QuickBooks Online 2023 Journal Report Get ready to start moving on up with QuickBooks Online. We're going to be using the free QuickBooks Online Test Drive Searching in our Online Search Engine for QuickBooks Online Test Drive Selecting the option that has Intuit.com and the URL Intuit being the owner of QuickBooks Support Accounting Instruction by clicking the link below giving you a free month membership to all of the content on our website broken out by category further broken out by course. Each course then organized in a logical reasonable fashion making it much more easy to find what you need than can be done on a YouTube page. We also include added resources such as Excel practice problems, PDF files and more like QuickBooks backup files when applicable. So once again click the link below for a free month membership to our website and all the content on it. We're going to be using the United States version of the software and verify that we're not a robot. We're not a robot. Scrolling in a bit by holding down control up on the scroll wheel currently at the one to five percent on the zoom in in the cog dropdown noting that we're in the accountant view as opposed to the business view we'll try to toggle back and forth between the two views so you can see where stuff's located in each of them. We're going to go to the tab up top right click on it and duplicate it as we do every time to put our major financial statement reports and the duplicated tabs right clicking again duplicating again tab to the middle opening up the reports on the left and then we're going to open the big balance sheet report as that's thinking tab to the right then tab to the left on the reports then open the profit and loss the P&L to the right that's the income statement closing the hamburger otherwise known as the hamburger changing the range from 010122 tab 123122 tab run it to refresh it tab to the middle close the boogie scroll to the top change the range 010122 tab 123122 tab and run it to refresh it that's the setup process that we do every time noting that these are the two major financial statement reports all other reports mainly are given more information about one or multiple line items in these two major reports this time we're going to open up the journal report so to do that let's go to the tab to the right right click on it duplicate the tab one more time so that we can go to the reports on the left hand side one more time so that I can close the hamburger up top possibly not for the last time and then I'm going to scroll all the way down to where we have the accounting reports which has been our focus the reports for the accountant we're going to be opening up the journal report in prior presentations we've been focusing in on these detailed reports that give us the activity that has happened through a period the classic one would be the general ledger that comes to most people's mind as the report that gives us all of the detail that breaks out first by account and then within each account it gives us the activity within it by date it's a similar report as we saw in a prior presentation to taking one of the accounts on the balance sheet in the income statement and drilling down on it except that it has all of the accounts kind of listed in it the great thing about software is that we can reorganize this similar data in different ways so we can take that activity and for example they have a report here the transaction list by date and then you got the transaction list with the splits so instead of breaking out this information by account and then date we got it broken out here by just dates we can look at all the transactions by date which can be useful for multiple factors and then we got the transaction list with the splits that gives us more detail and then the journal report also similar to it so let's do some comparing and contrasting with these three reports because they're similar in nature I'm going to right click and open the journal report in a new tab and I'm going to try to give a quick recap again of how this thing works so let's say that I just have the activity for December let's say so I'm going to go from 12-1-2-2 to 12-3-1-2-2 to 12-3-1-2-2 and so there we have it and so there's the activity for the month of December broken out by date now what that means from a financial standpoint notice if I go to the balance sheet and if I went up top I'm going to do one of those comparative reports comparing November and December so I'm going to first set the range for December 12-1-2-2 to 12-31 and then I'm going to say prior period and look at the dollar change prior period dollar change so now this is where we stand as of the December and this is where we stood as of November the difference between the two is the activity that's what has happened during the time frame so if for example we were looking at the November activity here and we knew that what that was and we can verify what that was and then we wanted to check our numbers on the December if we had the difference is going to be in this transactions all these transactions should be the difference so if we have the starting point correct and then we were to verify all of these transactions entered into the system we would get to then this ending point here that's the general idea now that of course is useful as with the prior reports to think about from a grading standpoint we'll use these kind of reports when we go through the practice problem because we can check where we started at then we're going to enter data into the practice problem and if your data is different than the data that we have you can look at these types of reports to see if your activity matches and if it does it should it should tie out or we should be able to find in essence the difference looking at the activity it's also a great report if you're kind of supervising someone else and you want to see how much act what they did right so you want to see how much activity they put into the system you can run a report like this you can basically charge see how much time it should take for charging that and you might use a report similar to this to bill like a client for example based on how many accounts were affected so you might count like this line this time to look at the number of accounts that are affected and you're going to set your billing range based on how many accounts were affected so if you had a hundred accounts affected I charge you this much if you had between a hundred and two hundred I charge you this month and so on and so forth those are a couple ways that you can use this it's also a quite practical report from just to learn the accounting because it gives you the debits and credits of each transaction so let's kind of compare it to the other two reports so if I go back on over here I have the transaction list by date report transaction list by date right click and open and I'm going to set the range up top on this one close on the hand boogie set the range from twelve oh one two two twelve thirty one two two and run it so there we have that it's a nice shorter streamlined report and so we start off with this cash transaction on twelve one for fifty two and there's the cash transaction here for fifty two let's look at the other one that's similar which is going to be the transaction list with splits right click on that duplicate and go to that report and then close the hand boogie scroll up I'm going to go from oh one oh one two two to twelve thirty one two two and run it and so now we have this one now this one's nice but it still gives it by by the account first the thing that's nice about it is it gives us the splits over here so it doesn't just tell us you know the other side of the transaction but gives us the multiple accounts that are impacted so if we had an account that has multiple things happening to it then you see the activity here but so it gives you the full transaction but it's but it's broken out by account so if we compare these then this this one we looked at last time is streamlined it gives it by date which is kind of neat I wish they'd give us this one by date that also has the splits but they've got this one by date and we can sort it by transaction type but we get where it gets a little bit tricky is that when you have these transactions that have a split in it such as this one well let's take a look at this one so because then you can see one side of the transaction but then there's more than two accounts on the other side so you get you lose a little bit of data but at the same time it's a little bit more streamlined of a report giving you all the transaction types in a nice tight kind of place if you go to the journal report then it's going to give you the detail in the format of debits and credits so that's nice because you can still see it by date over here and then you get the detail by date of all of the accounts that are impacted and you can kind of count the number of accounts in that fashion you can do so by exporting to Excel if you wanted to and use some kind of count if function in order to count the number of transactions if you wanted to use that it's kind of like a billing range that you can use because that will take into consideration these larger transactions that have more than two accounts affected also great tool if you're trying to understand the journal entries because this will give you not only the accounts that are affected it'll give you the accounts affected when more than two accounts are impacted and it's going to give you the debits and credits so you can start to look at these transactions and say okay what's an invoice actually doing in terms of increases decreases and debits and credits look at the transaction over here and then you can go verify that transaction what it's doing on the financial statements by going to the actual financial statements for example this one accounts receivable went up by 108 on 12 6 I can go into the accounts receivable and drill down on it and on 12 6 it should be going up somewhere by 108 I believe that's the one so we can kind of use this to get a better understanding of how each of the forms are entering a journal entry to create the financial statements and then we can kind of double check our debit and credit kind of format also understanding what these actual invoices are doing with a transaction you can see it can get quite complex the payroll transactions also can be quite complex so it's useful to go into these kind of transactions and understand them it's also possibly relevant from a billing perspective because you might want to say hey I'm going to charge more if I'm entering transactions that have a lot of accounts that are impacted for example and you can take into consideration that fact so like this invoice is obviously a lot more complex than entering an invoice that you just had to add like one service item or something like that so those are those general detail reports and we'll look at those and when we go through the practice problems to kind of verify our number let's go to the first tab I'm going to go to the cog dropdown switch to the business view just to see where we've been located and on the left hand side we've been just basically under the reports which is under the business overview reports up top


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One receiver on the side left here and a whole couple of centers on the right-hand side that have the public key corresponding to the secret key all the receiver and all the centers are interested in Picking messages and sending them to the receiver and they want to do that by means of public key encryption So what does it mean? They all pick fresh randomness encrypt the message and send it via some public channel to the it to the receiver Okay, so far so good. So what do we assume? Well, we assume that there's an adversary That observes everything that is sent on the channel meaning he sees all the ciphertexts Plus we assume that the adversary is capable of corrupting some of the senders What does corrupting mean? Well corrupting means the adversary will learn the message sent by these senders that he corrupted plus the randomness used to encrypt and the randomness Obtained by the adversary essentially lost the adversary to recompute and check that the message He just learned is actually contained in the ciphertext. He already observed Okay, and the question is well, what about their security or confidentiality of Messages that were sent by non corrupted parties. So for instance in our case. What about the confidentiality of message M2? Okay, so why is it interesting? Well, it dates back to a Paper published almost 20 years ago and back there it was considered for commitment schemes and called the selective decommitment problem And there's still lots of open questions going on. What makes it interesting is furthermore that the messages might depend on another So what does it mean is your message M2? As you message M2 depends on message and one and if some adversary Obtains the information message of one. He might already obtained some obtained some information on message M2 So we should rephrase do messages of uncorrupted parties remain confidential to do they remain as confidential as they can Okay for quite a long while we didn't know how standard security meaning CPI or CCI relates to selective opening security and Only recently. How friends and I could show that selective opening security whether you go for passive or active attacks is Actually strictly stronger than the standard counterpart of it Okay, so let's turn the scenario we are facing into a Proper security definition and we're going to do that by means of the real ideal paradigm And we're going to start with the real setting so on the left hand side There will be the real game on the right hand side the adversary Okay, so what is going to happen? The real game will generate a secret P will give the public key to the adversary and Really our interest in active attacks meaning the adversary will have access to a decryption oracle with the usual restrictions Okay, what's going to happen now? We allow the adversary to control the message distribution The senders will sample their messages from Okay, so the adversary picks picks the message distribution send us to the real game of the real game will sample and messages accordingly Now the real game will encrypt the messages and send them back to the adversary and Now we're going to model the corruption phase and for historical reasons. We're going to call the corruption phase opening phase So the adversary is allowed to make an open request and the game reveals message MI and Randomness our eye of send our eye Okay, and the address you can do this multiple times and eventually the adversary outputs something that we've just called out and The real game just returns out to and intuitively think of out as some information The adversity tried to derive on non-opened ciphertext Okay, and for the ideal game. We're just going to move Every artifact from public key encryption So we end up in such a game. So there's no key generation. There's no public he sent There's no encryption happening no access to the decryption article and The simulator which we call the adversary in the so the adversary and the real in the ideal game We just we labeled to a simulator Is allowed to make open crease but will only receive a message Okay, and when do we call some public encryption scheme secure well We call it simulation based selective opening CC a secure if you're every efficient adversary There's an efficient simulator that can essentially direct the same information what does it mean the Ciphertext that weren't opened didn't leak any information Otherwise, there wouldn't be a simulator being able to derive the same information as a Okay What I would like to do now is show you how public encryption is ideally done in practice How to obtain efficient public key encryption and This you usually do by the camdem approach meaning you want to use an asymmetric primitive to establish a symmetric key and Then you use some highly efficient mode of operation like counter mods cbc ccm gcm to encapsulate your data You want actually want to protect And this is what you would like to do to obtain efficient public key encryption and we already have some results on the Selective opening security of practical public key encryption Well, or maybe not so there's one paper by Hoya et al that took a look at the hashed algorithm and OAP and they could show that Both transformations or schemes are selective opening secure and a percent notion. We just saw However to obtain the result they had to instantiate in the case of DHIS for OAP It's already done by default. They had to instantiate the dam to be the one-time pad Which severely restricts the practicality of these schemes? because while you're limited to a Message length that corresponds to the output length of the hash function, okay Now I'd like to come back and show you how you could approach a proof for simulation by selective opening security so Remember that for every a we have to show that there exists a simulator that can drive essentially the same information So what we're going to do is we're going to take an adversary that runs in the real game and We will construct a simulator that will internally or internally run a and Can ideally direct the same information as they just by hot putting it And this has been done like that before and we follow this approach Okay, so let's have a closer look at the interaction that will happen on the right-hand side Okay, so the simulator will do something and At some point the address will output a message distribution would just relate to the ideal game then the ideal game will Do nothing because it's the ideal game and not the real game However, the simulator is to output ciphertext to the adversary then The adversary will post open queries which we can still forward The ideal game will answer the message and the simulator is supposed to answer the message and the random is used to encrypt the message and This will happen multiple times and eventually the adversary will output something and we just want to forward it and Well at this point here over here the simulator has to somehow come up with ciphertext and for now We're just going to call it fake ci so the simulator has to find a way to come up with ciphertext and When he eventually learns the message in this step and wants to reveal it to the adversary has to find a way to make sure that the Encryption you already committed to becomes an actual encryption of the message. She just obtained it wants to forward to the adversary Okay, we just call the second step make Okay, now I would like to show you what a practical data encapsulation mechanism looks like and And we're just going to take a look at the cbc mode plus a Mac So your message is pass into blocks passes through the block cipher and the opposite is x odd onto the next message entering the box after again and To obtain integrity. We are going to add a Mac and I want to point out that throughout this talk cable Do not the block cipher key and k prime will Donate some additional key material that will be used by for instance a Mac And if you just have a look at this picture somehow the cipher texts seem to be separated from the messages by the block cipher and This seems to be inherent to the construction of this data encapsulation mechanism And what we wanted to do is we wanted to abstract away the concrete block cipher and just study this Study the structure of the data encapsulation mechanism and this is why we went for the ideal cipher model So still the ideal cipher will be keyed by some key k and we are interested in the structure of the dam ignoring the block cipher that is used within the dam and This leads to the following definition that will help us to do a proof of selective opening security in the simulation definition and So this is Damn as I call it. It's not actually the damn in the paper We call it oracle damn, but for simplicity think of it as a damn But we abstract away the block cipher used within the dam and add it back as oracle access to the block cipher So it turns out to be some some encapsulation mechanism that has oracle access to the block cipher gets as input the additional key material and the message and outputs a cipher text and We are going to say that such a damn is simulatable if we have additional stateful algorithms fake and make Where fake just obtained obtains the additional key material, but not the message and is supposed to output a cipher text and Later on we have some algorithm make that can get information from fake cost their stateful and Get this input a message and it's supposed to output a permutation Okay, and we want to have the following properties namely If we run run fake on some key k prime We obtain a cipher text and then we run run make and obtain some permutation pi tilde Then we want that C is somewhat consistent and by somewhat consistent. I mean if we run the Damn encryption with access to pi tilde on M. We obtain C Plus we want that if we run that we obtain a uniform permutation as output by make Why is it supposed to be uniform because we want to patch it into the ideal cipher at some point? Okay So what can you do with the simulatable damn? well Let's build our way towards it So at the top there will be security notions for a cam below for a damn and at the bottom for some public key encryption So what is going to happen? We all know that if we take some CCS secure a cam and Combined with a one-time CCS secure a damn we obtain a CCS secure public key encryption scheme and As we know by result by the law at all we can break down One-time CCS security of a damn To see PA security plus one time integrity protection of the one-time integrity of the cipher text meaning we got One-time integrity guarantees for the damn Okay, and if you think what the simulatability does intuitively it allows you to come up with cipher text That are completely independent of a message And what you can actually show is that simulatability implies cpa security Okay, so what does it give us well if we stick to a CCS secure cam if we add one-time integrity of the cipher texts Additionally to the damn we should still obtain a CCS secure public key encryption This is all known But what we could show is that under these Given assumptions we can prove simulation based selective opening CCS security So somewhat simulatability allows us to go from CCS security to simulation based selective opening CCS security Okay, this is one of our contributions of the paper The second one would be that we study concrete data encapsulations mechanisms namely the ones standardized by NIST and What we obtain is like take any CCS secure cam Combined with any of these modes of operation You get a simulation by selective opening CCS secure public key encryption in the ideal cipher model You have to be careful when picking the damn cause some of them need to be equipped with a one-time Mac or something like that to obtain the Integrity the one-time integrity protection you would like to have Okay, so how do you prove such a statement? Okay, so let's get back to our picture where the simulator has to take care of the interaction between the ideal game and the adversary run inside the simulator and What I removed by the three dots is something like generation of public key and secret key of the key encapsulation mechanism Plus running the key encapsulation mechanism to obtain The symmetric key and expect encapsulation Okay, the adversary will output a message Distribution will just forward it and Now we can run our fake algorithm on the additional key information to obtain fake ciphertext that we can feed to the adversary then the adversary will like open crease we can just forward them and The ideal game will reveal message MI to the simulator Okay, but what can we do now? Well, we can use make to output a permutation and This permutation will be consistent such that if I run ink with access to pi I on message MI I will obtain the ciphertext CIS output by fake earlier Okay, and then I just take the permutation output by make and we'll patch it into the ideal cipher and then I should be fine I think this can happen multiple times and the randomness that is revealed here would be the randomness used by the key encapsulation mechanism and Eventually the adversary will output out and I'm just going to forward that Make sense Yes, so actually this is yes This is cheating so make is actually not so would be sufficient for make to not output a full permutation but just the the spots in the permutation relevant for Making sure that M Is an encryption? Sorry is the message contained in some ciphertext C so what will actually happen is that make will output something we call a partial permutation and The environment outside of make which will be the simulator in our case will put this part total permutation into the ideal cipher and Will fill up the ideal cipher on the fly by lazy sampling. So yes make is supposed to Partial permutation only. Okay. I'm going to skip over Sorry so I Guess intuitively it makes sense because make and fake are designed such that it's supposed to work the only thing I glossed over is that we want to patch the permutation into the ideal cipher and It's actually not clear if we can do that Because the adversary so what do we have to do we have to make sure that? To patch pie into the ideal cipher the ideal cipher has to be sufficiently free and What I mean by sufficiently free is that it would? suffice For the ideal cipher to be free at the spots where we would like to embed the partial permutation However, it's easy to argue that the whole permutation Ick will be empty and Twice that well at some point we should use the security guarantees of the chem and the dem and this is exactly where they come into play and Just to give you some more detail on that so an ideal cipher is It is a keyed random permutation where for each key got a random permutation and I'm going to denote a key encapsulation of the block cipher key And the additional key material just by K K prime in a box. So think of this as a CCA secure box Okay, and if you use this notion a hybrid encryption of M will contain the first component the chem part That contains the block cipher key and the additional key material plus the data encapsulation that has oracle access to ideal cipher K and Key material K prime and the message Okay, and we want to ensure That the ideal cipher K remains un-evaluated until the adversary opens The respective cipher text so as soon as this happens We can we can we being the simulator we learn the message can run make and Bet the permutation and then we should be fine So we just have to guarantee that until open the adversary will not query any entry in IC in the ideal permutation Okay Okay, so how do we do that? Well intuitively CCA security of the chem will ensure that if the adversary sees the encapsulation of K K prime cannot obtain K or K prime from it So you shouldn't be able to query the ideal cipher on key K and Then we got the damn and another way for the adversary to force an evaluation would be to submit decryption queries that Use as first in entry the encapsulation of K K prime and some other component and Assuming we would process such a query to by decryption We might evaluate the ideal cipher on K On on the permutation K However, the one-time integrity of cipher texts will ensure that we can just Return bought of such a decryption trees And this is why we need the similarity plus the CCA security of the chem and the one-time integrity of cipher texts by the damn which is Yeah, we'll get a bit in a second Okay, so what did we see? so we defined a Structural property of the simulator bill of Dems, which we call simulatability and What does it allows? Well Simulatability seems to lift the security of hybrid encryption schemes from Standard CCA security to simulation based selective opening CCA security Somewhat without additional assumptions, so we have to use the simulatability as another assumption But CCA security plus the one-time security of the the CCA security of the chem plus the one-time integrity of the Dem Have to be assumed to construct CCA security and on top of that we need simulatability of the damn to get to Selective opening CCA security however for lots of practical Dems Simulatability is given So what does it mean for lots of really practical public encryption schemes obtained by the hybrid chem damn paradigm We actually get simulation based selective opening CCA security for free in the ideal cipher model Thanks for your attention. You can find the paper on e print And if there are any questions, I'm happy to answer them and greetings to both of them Give me much. Do you have comment or questions? Can you provide some intuition why this isn't implied by standard? Sorry semantic security even for the CPA case well usually your encryption is committing and Once it is committing it's Impossible to output a cipher text, so I just need a while to get back So what we have to have here is that we want to output cipher texts without knowing the underlying message and Only later on we learn the message and somewhat have to fix it and as soon as the cipher text is committing there's no way To find randomness such that Okay, maybe for the one-time better for practical Data encapsulation mechanisms. It's highly unlikely that you will be able for to open a cipher text for any message Any other comments or questions? Yeah, the assumption are they kind of random or it has cipher random or it's the model and then as a Minimal assumption is that you need to have dropped or dropped the function, right? because they In the public encryption scheme when they came it's It doesn't have to have any Simulability correct. Yeah, so yeah, that's the thing. I I don't know a lot about simulation Selective opening, but what are the minimal assumption for selective opening? Can you do it from trapdoor function or do you need like? Lossy if you're So things that actually if you've gone to go on to go for a standard model results And if you just want to go for let's say selective opening CPA security any new tools like lossy encryption meaning you need lossy trapdoor functions to construct that an alternative would be to go for scheme spelling trip bit wise In practice, you don't want to consider them Well, do you mean a bit wise you mean that well thing is if you encrypt bit wise You might have a chance to find randomness such that a Message combined with this randomness becomes an encryption of the ciphertext you already committed to Just because your message message space is real small There's a notion of committing public encryption as as soon as you go for that You can't be simulation by selective opening secure any other comments or questions quick one. I Just have one quick comment our question Does your technique extend to the receiver select few opening results security results possibly? Okay. Thank you. Okay. Let's thank the speaker game the last talk of this session is Selective opening security in the presence of randomness failures. Those are the beats turn one Johnson cuts the money and Mohammed the hay and Adam will give a talk so I'm going to talk about Selective opening security in the presence of randomness failures. I guess


Luke, dwi'n fawr i'ch beth. Dei, ymlaen, ystod yw'i gweithio'r FRADFORD. Rydw i'r fawr yma o'r gallu'r fawr ymlaen y peth, ac mae'n fawr yn cynnig? Mae'n gweithio'n gweithio eich ffyrdd, ond rwy'n fawr i'r gwneud fe wnaeth i'r fawr i'r gyffredinol. Ac oeddwn ni'n gwybod am yr oedd yma, rydw i'r FRADFORD a'r dechrau'r gwrs. Felly, rydw i'n gweithio'n gweithio'r fawr i'r gweithio. We know you've had your time at Peter Bell last season, but obviously moving to this season with Bradford. What are your hopes and your aims really for this long period? Hopefully I can show people what I can do, hopefully a few goals and a few assists as well. I mean obviously it's really good squad of lards here and we'll be looking to do things this season and hopefully that will be a big part of it. Do you know much about the squad? Certainly particularly the fellow striker you feel up against, James Hanson, Steve Davies, certainly would have thought, hopefully fingers crossed looking to pick up some of their knock downs and look towards their service. Equally Billy Clark as well, obviously some of his link up play. Yeah definitely, any strike I'll try and help, I'll try and let them help me. I mean if you're playing up front with somebody you need to have a partnership and obviously one day you'll be helping them, the next day they'll be helping you if you're having a bad day and stuff. So yeah I just can't wait to get to cracking with the lards here. Is it nice that it's done relatively early into pre-season? I mean obviously what are we, three, four weeks until the start of the season? So you've got a chance to bed in, obviously we've got the Scotland tour coming up. A chance to get to know your team mates, get to know the flow of the club really as it sounds towards a good couple of weeks before the start of the season. To be fair hopefully I think myself personally it's a perfect time. I mean obviously we're going away Scotland next week so that will give us a good opportunity to get another lards, obviously I'll be spending day and day out with them so I can only say is it positive coming this earlier. And feel the North East lads, you're not the only one in the squad maybe. Tag along with a few of them journeys up and down the training ground. Yeah maybe, before I've been talking about what to do, especially with Lids and Tony as well but yeah I can't wait to get going and hopefully it'll be a good season.


In this class, we will talk about FFT analysis which is fast Fourier transform analysis or FFT in brief. Like in the last class, we have seen that we have been able to store this digitally acquired data on the computer's RAM memory. So, from here how do we estimate or analyze the signal to find out its frequency components and that is what we will do. Well, to briefly review, we had discussed this in the past that even before FFT analysis was available, we could still estimate the frequency of the signal by signal filtering by having analog filters. It could be band pass filters, low pass filters. Now, we will talk about octave and one-third octave filters later on when we talk about audio signals. And then we had discussed about signal heterodyning wherein the phenomena of beat was taken into advantage to know the frequency of an unknown signal provided we have we know the frequency of a reference signal. And then orbit analysis using Lissa-Jose figure wherein we can compare the ratio frequency ratios of signals. And of course, mathematically if the function is periodic is mathematically describable, we could use the expansion of Fourier series as to find out the frequency content in the signal. For example, I should tell you when we do Fourier series though, we had find out this coefficients a naught, a n and b n. So, a naught is actually independent on frequency and this is known as the DC component of the signal or what is known as the mean component of the signal. But because of the limitations of Fourier series as if the signal could not may not be continuous, may not be periodic etcetera, we have the Fourier transform wherein Fourier transform can be in the forward direction from the time to the frequency domain Fourier transform. And if I have an inverse Fourier transform, I can get the time from the frequency domain. But this Fourier transform can be done mathematically because if you look at the signal x k, this is nothing but the digital representation of this transformation from the time to the frequency domain. I will explain you what this is because this is an equivalent of the Fourier transform. And if you look at this equation, the integration has been replaced by a summation sign. So, this can be very easily implemented in a computer and if the data, these are the x n is the digitally sampled time data, capital N is the number of data points digitally acquired. You know this n is what are specifying to the memory space in the a to d card. Small n is a time index which goes from n is equal to 0 to n minus 1. So, it covers all the n data points and k is similarly a small k is similarly a frequency index. So, this is in the time domain and this is the frequency components. So, let us see if you want to do this operations and these are complex numbers and these are complex in nature. So, a real world time domain data will have complex Fourier or frequency domain components. And this competition is complex. So, actually what happens if you look into this number of operations, there are actually in this DFT, discrete Fourier transform there are n square complex operations. But you know in I am talking about before the advancement of computers and you can understand to do n square complex operations, it was a Herculean task. You are talking about the year of 30s and 40s you know during the world war etcetera. How do you think people analyze signals? This is a very very difficult task. I will give you a brief history of Fourier analysis. So, actually in 1964 two gentlemen working in the IBM Research Center in New York known by gentlemen Cooley and Take they came up with an algorithm where n it was not n square complex operations, but n log to the base 10 of n operations to do DFT. And in those days you know computation was very expensive. So, but this when n n square is a parabola with n log n this is the n log n n square computation time or resources. So, this was a much faster way of doing the same DFT and this gave rise to a fast way of doing discrete Fourier transform. And this then came to known as the fast Fourier transform. In those days you know what event today you are you know the calculations you can do on your mobile for and on your calculator you are done in computers which are you know as big as this room. So, you can imagine the amount of computational effort required to do a Fourier analysis. Nowadays on your on your laptop if you do DFT or FFT you will hardly know the difference between the computation time and n could be as high as you know 10 to the power 12 or 10 to the power 14 it is not a problem. So, but in those days you know in 1964 not very far off, but then this was a problem. So, actually to give a little more history about this FFT. So, this Cooley and Tuckay once they came up with this algorithm the company and of which we know all the HP Hewlett and Packard they came up this that is what we have read in history that they hired Cooley and Tuckay and started selling FFT analyzer. So, having the Cooley and Tuckay algorithm in them. So, they left IBM and they joined HP, HP started marketing the FFT analyzers from the late 60s and they were very very popular event till few years ago, but nowadays you know we have you know chip based or card based FFT analyzers. Those days the FFT analyzers was size of steel aluminum mirror, large steel aluminum. Nowadays the FFT analyzers could be as small as your you know cigarette lighter and they will be much more powerful, because such has been the advancement in electronics that fast chips VLSI chips etcetera we can do this mathematical computations on the hardware very quickly and then come up with the FFT results. Well, so what is FFT? FFT is nothing but an efficient algorithm to do DFT, but what does FFT gave us is very important, because to begin with I have a block of sample data 0 and to n. So, I have n minus 1 to be precise I have this data's which are there on my I am denoting them by circles, because this is what I have obtained after my data has been sampled. So, this will corresponds to each of your x n and then I will have an such an array of n data points and all I need to do is I need to sample it at a time index, where n times delta t where delta t is the sampling interval. So, I will n is equal to 1 times delta t 2 times delta t 3 times delta t and then I will pick up all this successive values and plug it into the equation of DFT and do the operations using the either the n log n operations or the n square operations and come up with components which will be nothing but the Fourier components of such signal. So, if I was to now explain to in a block diagram I will have and I will get this is in time, this is in frequency and this is the FFT process. So, this is the digitally sampled data and this is the complex and this is usually a real data, it is not a complex number because real world signals are real not complex, but I will have a complex I will say Fourier or frequency components. So, X F being a complex I can represent as and this is in the frequency domain, but then I need to know what is the relationship between this time and frequency. For example, if I have n blocks of time data in the frequency domain what happens is 0 component it goes to n by 2 and may be n by 2 minus 1 etcetera. So, this component I will have n by 2 minus 1 etcetera. So, these components will almost be a mirror image mirror image and this is in the frequency and this is in the time domain. This could be sought in the negative frequency and this is in the positive frequency. For real world signals we actually discard this data we do not use this data. So, any n data point will have give us only n by 2 meaningful FFT results. Now, so how do we relate to the sampling frequency to the maximum frequency contained in the signal to the spectrum which we get in the frequency domain. I should tell you like we have time waveform where the X axis is the frequency we call anything as a spectrum where the X axis is the frequency. So, this complex numbers which we will get. So, the magnitude of this is nothing, but and then of course, there will be a phase between the real and imaginary. So, phase is nothing, but tangent inverse of a phase is also a function of frequency. So, I am denoting through a magnitude phase or real imaginary. Now, we will see before we see the relationship let us see what certain terminologies in this FFT mean and they all will relate to the my original FS because we all know what FS is the sampling frequency and we know how it was related to the feature it is a property of the data equation card and sampling interval related to this. If number of data points is n total time t is nothing, but n times delta t is nothing, but the time record length because I can I have to rather do FFT on a block of sample data. So, this is my block of sample data. So, this is maybe I will I can either start with 1 and n and then this distance between them is delta t total time here is n times delta t is equal to t this is n time domain. Now, once we do FFT this will be converted from the frequency domain and let us see if I was to plot the results of FFT. So, we put the amplitude of this and I am getting a plot like this wherein I have joined all the frequency components. So, there are all these individual frequency points I will not complete this, but so this is now not equal to delta t, but this is delta F and which is the frequency resolution. There is a very fundamental relationship between this frequency resolution and time. They are inversely related and the most important equation is this delta F is nothing, but 1 by capital T. I do it is not delta t, but capital T. So, the more the time you have a long time you can have very fine resolutions. You can imagine if I want to see frequencies every 0.1 hertz, 0.2 hertz, 0.3 hertz how much of time do I require. So, because delta F is equal to 1 by n delta t because t is equal to n times delta t. So, this is nothing, but sampling frequency by n. So, if my sampling frequency is fixed I can have only a lower resolution or improved resolution if my n is large. So, large amounts of data needs to be taken to have a finer details of the frequency and this is something you have to keep in mind while setting up your FFT analyzers to do the calculations. And then I hope this is clear to all of you and then this is very important here how the frequency resolution is related to the sampling frequency and number of data points. Now, as I was telling you once we have n data points we will have 1 going from minus n by 2 to n by 2. This is the negative frequencies which we discard. So, the maximum frequency in the F max or in the FFT will be from 0 to this is this value is only n by 2. So, the maximum frequency F max which we obtained in this frequency is nothing, but k times n by 2 and what is this k? I am sorry delta f times n by 2 with each one of them is delta f. Now, delta f is nothing, but f s by n times n by 2 that is equal to f s by 2. So, given a sampling frequency I can very well almost obtain half of it. So, when I am talking about an analyzing an audio signal in a out of a CD player coming out at 20 kilohertz I should sample at 40 kilohertz and above.  So, usually we sample at a value of 2.56 times F max. So, if n is equal to 1024 data points in the time domain, we will have 512 points in the frequency domain of interest to us. We will discard the few points at the last. So, we will have what is known as when n is equal to 1024 n by 2 is 512, but we will take actual n is 400 and it is 2048 this will become 1024 this will become 800 and this are commercially known as lines of FFT. This means in my FFT analyzer I will only show you 800 or 400 or 200 data points. So, reference is an indirect way of telling that how much data I would have taken in my n. If it is 800 I would have taken 2048. So, nowadays there are analyzers wherein we can have up to 7200 lines of FFT. And this means 2048 blocks of data sorry data points in a block are taken and the FFT analysis done and the results displayed. Nowadays FFT analyzers I can either do it through the software given by that equation or even implement it in a hardware or where all this hardware competitions are done. FFT competitions also takes the time. Imagine I have taken a block of data of n points. So, I have to do FFT on this FFT takes some computation time. So, because if this is a continuous stream of data coming in I am taking blocks of data blocks of data. So, before I finish computing the FFT if more data comes I am going to either store I have to either store them otherwise I will lose the data. But if I can do the FFT complete the FFT before this second block of data comes I would have done what is known as the real time FFT. So, FFT competitions are done on the fly on the run quickly efficiently before the next block of data comes to my block and that is what is known as real time FFT. And then analyze the processing has to be very fast. Nowadays you know the computers are very fast. So, we can do it very quickly and then there are software which will guide you to you know suppose there will be a buffer management in the sense suppose you are taking more time. So, this will come and hold this data somewhere till your FFT is complete and so on. So, this kind of management is done in a software also. But now coming back to this FFT. So, maximum frequency which we can analyze is nothing, but f s by 2. Now how do we ensure that the FFT which we have done is correct. For example, let us take the case of a sine wave. So, for clarity I am drawing all the lines this is contained in such blocks of data and then I am having doing an FFT. So, if this was a pure tone signal in the FFT if I was just to plot the magnitude of this it has. So, I should be seeing one peak and this should be of 10 volt and the frequency corresponding to the frequency of the signal the magnitude of the signal. But you will see some instances what happens I will go into the specific details. For example, this is of a frequency of 23 hertz. So, I should be having a delta f and if I have taken delta f is nothing, but your f s by n is not it. So, if my f s is say 1000 hertz and I have taken n as 100 hertz. So, this is my delta f becomes 10 hertz. So, obviously, this computer is going to understand 0 hertz 10 hertz 30 hertz 40 hertz and so on. So, when it comes to 23 hertz it is lost like we had then the amplitude resolution case whether this is a 10 hertz signal I am sorry it will be 20 here also whether it is a 20 hertz signal or a 30 hertz signal. So, this is what is known as the picket fence that means I have inadequate frequency resolution in my signal. So, to overcome this I need to have my frequency resolution very very less that can be done by increasing the number of blocks of data number of lines of f f t same signal if you do an analysis with different blocks of data or lines of f f t you will sometimes get a sharp peak sometimes you will not get a sharp peak. So, whenever you are looking for unknown frequencies it is a good rule of thumb to have a final resolution. If you do not see any frequency spikes coming up you know you are not missing any signal otherwise you are going to miss a signal. So, when you use an f f t analysis that we have to be careful to play around with the signal change the setting see the number of blocks. How I can reduce the increase the block size of course, in increasing the block size means more time well and good, but then I should not be missing any frequencies. There are signals you know particularly when you have you know the space shuttle etcetera very massive bodies you know there will be natural frequency of the order of less than 1 hertz maybe 1 is having 0.7 hertz another is 0.09 hertz low frequencies at 2. So, distinct and closely spaced frequencies. So, if I get a vibration signal from a space shuttle I should be able to distinguish between 0.07 hertz and 0.09 hertz. So, this is a challenge to do. So, we have to have adequate frequency resolutions to ensure that this picket fence effect does not occur and we somehow miss the signal. This comes from the name of the English picket fence in the sense you know and if you have seen the English picket fence there are no white color pegs. People have it on the English side and there is the fencing. So, if I was to miss something if I was to hit a cricket ball cricket ball will pass if this fences are wide apart this pegs are wide apart, but I will catch it if it is they are close by. So, this is what is known as the picket fence effect in FFT. So, once we have a final resolution we are going to catch the signal. So, this is to be avoided by having adequate frequency resolution by increasing the number of data points. Another effect of the FFT is what is known as the leakage error and this has a serious effect in the amplitude estimation of the signal. For example, the FFT analysis it takes a block of data and it assumes that this blocks repeats itself assumes a periodicity because I have this data is coming I have started sampling the data I picked up the data and one it comes to end data points I stop it I clip it. Now, if my this data was a continuous sine wave. So, if I put few windows here sample the signal by this red blocks red boxes and you will see each one of this starts at a different starts and stops at a different amplitude location. For example, this has started here this has started here. So, this creates an amplitude discontinuity. Now, to avoid this discontinuity of what we do. So, there is what is known as a leakage in the frequencies. So, if my actual frequency is this the computer would estimate it is this because of leakage error. This is avoided if I multiply it with a function dot product because this is the sample data x if I multiply x with a windowing function wherein the window function looks something like this. So, at all the end points it multiplies them and makes them 0. So, this discontinues discontinuities are avoided by multiplying it with such a windowing function. So, that the leakage is reduced and then we will get a better estimate of the amplitude. So, with windowing I will get as close to the because you know here you see because of the leakage my right correct amplitude is given by this red signal x, but because of leakage I am getting this signal. So, this is a wrong estimation of the amplitude of the signal and sometimes also wrong estimation of the frequency because you do not know whether to take this frequency this frequency this frequency and so on. So, a wrong estimation of both frequency and amplitude is obtained because of such discontinuities because it assumes a periodicity. So, we multiply it with a windowing function to reduce this discontinuity, reduce the leakage and get a better estimate. There are many such mathematical windowing functions and I will write you the name of some of these mathematical functions. One is no window or this is a rectangular window handing is another very popular window and this is a flat top and there is an exponential window. Rectangular window is for it is actually a no window it is just a rectangular function and this is for a good frequency estimation of periodic signals, this is for a good amplitude estimation and then this is for removing transients. For example, in the fourth example suppose I have a signal wherein lot of oscillations are there. So, I could put an exponential window like this, this is used for for example, if I have excited a structure I want to see it is response, response would have died down because of damping I can reduce this ringing effect. So, that I bring it to 0 discontinuities are not removed or made to a minimum and for periodic signals we conventionally use either handing or flat top. If I want a good amplitude estimation of the signal I should use a flat top window in the FFT if I have to use a good estimation in fact, the correct estimation the frequency I should use a handing window. So, in the FFT process if I have taken care of this inadequate frequency resolution by having increasing the number of lines of FFT or increasing the block size I would be able to capture any unknown signal which would have otherwise would have missed. Another is to have a right estimation of either the frequency or the amplitude of the signal or windowing function has to be used. Now, this FFT which we have obtained can be either represented in the. So, this is a complex quantity this is the real quantity and then imaginary quantity this is the rectangular method of. So, I will have the real part of X F and then imaginary part of and you know how this F is related to nothing, but k times delta F per k is 0 to n by 2. k varies from 0 to n by 2 this is k is equal to 0 to n by 2. So, I will get the frequency spectrum both are really imaginary and then I can represent them in the polar form like by the magnitude and the theta. Now, what does this convey to us FFT physically what does it convey to us other than the frequency of the signal? This signal also carries certain information as to the energy contained in the signal as to the energy as a function of time as to the power of the signal. So, from the frequency after the FFT lot of post processing is done to the signal to analyze what other information we can obtain from the signal. So, let us see some of the signals some of the quantities which we can obtain from this FFT. So, if this FFT has been obtained I can obtain the linear spectrum magnitude of the linear spectrum is nothing, but so unit becomes linear and you will see magnitude means this is a real quantity and another quantity which we use is the auto spectrum or auto power spectrum of the signal sometimes power this means it is defined by this notation X capital S X X F is nothing, but the FFT of the signal multiply be careful this is a multiplication signal by it is complex quantity conjugate complex conjugate. So, this we will boil down to if I if I will not use the R I F notation.  So, this will be nothing, but so you see though the FFT is complex the auto power spectrum is a real quantity and linear spectrum is nothing, but the square root of auto power spectrum it will be just the square root of this in which we have obtained here and mind you they are all functions of frequency. So, the auto power spectrum conveys how much of energy is there in that signal another related is the power spectral density. So, this is given by auto power spectrum by delta F. So, unit will be voltage square by say hertz and this is used to characterize random signal which are varying with time. So, linear spectrum will nothing, but the square root of power spectral density. So, this will be so this units will be voltage by square root of hertz. So, these are certain quantities which are can be very easily calculated from the after post processing the signals and this is just for one signal, but if there are two signals we can find out the correlations between them and how they are related to each other. And many of the FFT analyzers will have this availability at the push of a button even in the softwares, but we should understand what physically they mean. So, we started with the signal x t we have seen how we have sampled it got the blocks of data x n done FFT got x f from x f we have got s x x and then we have got the auto power spectrum. Now, let us see when there are two signals we will have what is known as the cross spectrum suppose I have two signals x t and y t and usually in a mechanical system this can be very easily related to suppose my input signal is x t output signal is y t and for a mechanical system to know the linear relationships between the stick to signals whether one is causing the other to see the causal relationship between the output and input I can look into many forms. One is the cross spectrum s x y as a function of f is defined as the auto spectrum of x multiplied by the complex conjugate of f and you will see that this is a complex quantity the power spectrum was real quantity, but the cross spectrum between two signals x and y is a complex quantity.  So, this is also a complex quantity. So, this will have magnitude and phase or real and imaginary part because these are all complex quantities. So, now let us see how we can calculate the frequency response function from the cross spectrum and auto power spectrum. So, f r f can be written as y f by x f this I can write it as this means what I have. So, the frequency response function can be computed as the cross spectrum divided by the auto power spectrum of the input cross spectrum between the output and divide by the auto power spectrum of the input. Now, there is another quantity which you have how are x and y related like in statistics you must have studied about coefficient of co relation if I plot x and y if they are very close by I will say they are nicely correlated in the time domain. Here also in frequency domain we can find out a term known as coherence gamma square f given by s x y f square divided by s x x f s y y f and the maximum value of this could be 1. If I plot the coherence as a function of frequency this will may be if it is like this I can say that at some frequencies the output is not because of the input. So, this has a very very important application in machinery diagnostics and we will see that in the subsequent classes as to how the estimation of coherence frequency response function and cross spectrum can be used to understand whether the output y has been caused by x whether a defect which is notice in y is because of x this can be found out by this coherence. And in machinery condition monitoring when we measure signals from machines we will be trying to find out the coherence between the input and the output between two transducer locations whether one is causing the other and this is a very powerful way of diagnosing or finding the source of a fault. We will be seeing the applications of FFT in the subsequent classes and this was just the basics about the FFT and how we can avoid errors in FFT particularly the frequency resolution and the effects of windowing and then what are the post processing features of the FFT which will be useful for machinery condition monitoring. And then another aspect of FFT is you know I want to still with the available resources I want to see much finer details. So, that can be always increased either you decrease the sampling resolution or increase the time record. So, sometimes decreasing sampling frequency may not be a possible then we have to increase the time record. Thank you.


Now from a vice president to Ticco, Bobacus says where the president comes from has never been dissolution to the series of problems facing the nation. He stated that the next president can come from any region as his party moves to reclaim power at the center come 2023. A Ticco made a remark at the meeting of the Peter Pan National Executive Committee held at the party's national headquarters in Abuja. Addressing members of the party's highest decision-making body who approved their recommendations of the PDP zoning committee, he asked them to be fair and just in deciding where the party's presidential candidate would come from. There is no such thing as a president from southern Nigeria or a president from northern Nigeria. There is only one a president from Nigeria for Nigeria by Nigerians. Talking about inclusions, I would like to see a new national working committee of our party our great party that has sizeable numbers of our youth and women. The decision of NET today will either see us PDP into the villa in 2023 or not. Since the inception, this party has faced serious challenges and have risen above sentiments to solve those challenges and move forward.


Five seconds remaining. Never refuse gold given. Dyer's bottom tower is under attack. Five seconds remaining. For refuse gold given. Dyer's bottom tower is under attack. Never refuse gold given. Dyer's bottom tower is under attack. Innscurrier has been killed.


Hi everybody, I'm Don Sweeting, president of Colorado Christian University, and we are just getting ready to finish our academic year. It's amazing when you think back and consider all that's happened in this academic year because it's been so unprecedented with the adjustments to be made for the pandemic. And yet we look back with incredible thankfulness. Why? Well, because last spring, this time, we were praying for wisdom, asking God to show us how to go forward, and we took a step of faith, opening up in the fall, and then opening up in the spring with in-person training. And now we look back and we are so glad we did. In fact, I haven't met one student who's regretted being here this year. It's interesting, as I talked to some other university presidents, some have not been open this year and they're wondering whether they should be open next fall. And we're just on very different tracks. We look back with thankfulness to our faculty, our staff, for all the adjustments they made adopting protocols that worked, adopting a high-flex model of education that worked. We're thankful for our students who stepped out and they're here. They didn't want to put their future on hold, and they've had an extraordinary academic year. This has been our 11th consecutive year of record enrollments. We don't want to put our mission on hold, our mission of Christ-centered higher education, transforming students to impact the world with grace and truth. So here we are, and commencement's coming in just a few short weeks. An in-person, outdoor, live commencement. And now we're ready to pivot, looking forward to the next academic year, the 2021-2022 academic year. And we know things are going to be closer to normal than they've been this whole year. We look forward to having a robust schedule of campus activities, look forward to having in-person instruction, in-person chapels, in-person academic lectures, in-person music events and athletic events. We're going forward, full steam ahead. We look forward to having student retreats and the things that we've missed so badly. So as we look to this next academic year, we have a feeling it's going to be over the top, way beyond even this year. And we're asking God to do an extraordinary thing on our campus in the lives of our students. I just want you to know that.  I want you to know our intentions. I want you to know God's goodness to us this past year. And I want you to pray for Colorado Christian University as we look forward to fulfilling this strategic, important mission of raising up leaders for Christ and His Kingdom.


G'day, May 40 here. So just reading an article in New York Times, Molly Jong Fast. She is the daughter of Erika Jong and here's the article, how Molly Jong Fast tweeted her way to Stardom. And I interviewed her back in 2004. I was doing a whole series of interviews on American Jewish literature and she was one of the Jewish novelists that I interviewed. So why has Molly Jong Fast been able to tweet her way to Stardom? For say, Kyrie Irving and Kanye West got into a ton of trouble recently and a lot of it simply has to do with likability. Like, Molly Jong Fast is incredibly likable. She's incredibly open about her struggles with addiction and I knew she was a lefty when I interviewed her and she knew I was on the right. But she was just incredibly charming and pleasant and fun to talk to. And people like Kyrie Irving and Kanye West, they're just not very nice. Not just very fun. Not exactly fun to talk to. They're difficult people. Molly Jong Young, not such a difficult person. She's very easy to get along with. And so people like easy. So how Molly Jong Fast tweeted her way to liberal Stardom. She wasn't a political expert, but a Trump-era angst found her following among Democrats and even the White House is interested. So she just, the story begins with her interviewing Vice President Kamala Harris. And she tells the owner of the New Republic, Win McCormack. Oh, I just interviewed the Vice President. And McCormack replies, brow-firing the Vice President of the United States. So Erica Jong Fast, 44, she is perhaps best known for being the daughter of her mother, Erica Jong. She wrote the classic feminist novel, Fear of Flying. So Molly Jong Fast went into rehab at 19. She got married at age 23. She read a couple of novels. That's why I interviewed her. She read a book of essays about her bohemia by way of Park Avenue upbringing. Now she's a liberal media star. So how did she do it?  So this week she joined Vanity Fair as a special correspondent. One million people follow her on Twitter. Her podcast is distributed by iHeartMedia. Her first guest was Ron Klain, President Joe Biden's chief of staff. She's interviewed all sorts of senators like Bernie Sanders, Chuck Schumer. She's interviewed Julia, Louise Dreyfus, John Fetterman, Kamala Harris. She's interviewed people like MSNBC lineup. So her ascent is a little bit like the Woody Allen movie, Purple Rose of Cairo, where she steps into the screen and enters the world of her favorite film. So she marshaled her weapons-grade Twitter habit. And her networking ability, she just slide into journalists DMs.  She's an MSNBC mom who appears on MSNBC. So part of it, in the big picture you say, oh it's because of the growing importance of social media. But a darn lot of it, it's just that she's so likable. You can be right-wing and enjoy a conversation with Molly Jung first. She is not pompous. And a lot of it is that professional pundit tree does not require unique rare skills. There's not a big difference between armchair pundits and professional pundits. This is a woman who's likable and a great networker. She wins friends easily. She wears her privilege lightly. And she has incredible empathy and charm. And most people who rise to media stardom are pretty good at being charming. Richard Spencer was charming. Nick Fuentes charming. The power of likability. Noah Shackman is now the editor of Rolling Stones. Noah wrote three articles about me back in the year 2000 and 2001. Now he's the editor of Rolling Stone. Like when he came to LA we used to go to social gatherings together. He introduced him to Andrew Breitbart and a whole bunch of that crew. So now Noah Shackman has done good. He's like, there's this economics writer for the New York Times. I used to, Adam, Adam, blanking on his name. He used to know him 20 years ago. He introduced himself to me, he showed me around. He's gone on to great success now with the New York Times regular column, I think, weekly on the economy for the New York Times. So she's not adversarial, she's nice. So one big reason why Molly Jung Fast is successful in curry Irving and Kanye West is struggling. So Kanye and Carrie are not very nice. And one key to likability is just Molly Jung Fast is just incredibly open. People generally speak like people are open and honest. People like people are willing to be vulnerable. People like people who open up. So she says, I was a drug addict and nearly died. I got sober. I've had this incredible run. She's grateful. People like people who are grateful. So her grandparents include Howard Fast, the novelist of Spartacus fame and communist. He served in prison time during the McCarthy era. And her mother, Erica Jung, was an early adopter of oversharing. So in 1985, Erica Jung moved six-year-old Molly Jung into the Beverly Hilton for a month because Erica was developing a sitcom based on her daughter's experience with divorce. So Molly Jung's father, Jonathan Fast sued Erica, his ex-wife, and demanded that the TV show change Molly's character's name from Molly to Megan. And a review in the New York Times praises the show's appealing breeziness. Molly Jung Fast is dyslexic. She did poorly in school. She got kicked out of Dalton, this elite private school. It was like a seismic shock to her intellectual family. She got into alcohol and drugs. She spent time at Hazelden, the atelist rehab center, and then published a novel about her struggles. I just did what my mother did, she says. I thought that's what you're supposed to do. The reviews were vicious. She then married her husband, who was an English professor turned venture capitalist. She had three children. She read another book. And Trump came down the escalator and it gave her life meaning, right? We're all looking for meaning in life. We all want to feel so we matter that we have significance. So Donald Trump came along and gave a ton of people meaning, whether they're pro or anti-Trump. So to be successful, it requires energy. And it's a lot easier to get energy if you feel that what you're doing is significant.  I need to tweet about my angst. And she hit a chord. She became incredibly successful. I had a bit of an interesting experience last night. So it was probably one in the morning or so. And I was up too late. And I was about to go to bed. And I clicked on this, I was just looking at Twitter. And I clicked on this space that was being recommended to me. And it had, you know, 250 people in it or something. And I was just kind of curious, actually. And I think the title was something like The Big Man Returns or something. So I was curious and then I realized immediately that it was Nick Fuentes who has a... He has some, you know, secret accounts towards it. He's disobeying Twitter's policy by creating new accounts. And there were a lot of people in there. And it was only, I mean, by the time I realized that it was Nick Fuentes, you know, in a matter of, say, 30 seconds or so. They were like, oh, Spencer's in the chat or whatever, you know. And they were like, we've got to get him out here. Accept the request. But I did. And I was expecting a kind of like, you know, blowtorch treatment by Fuentes. It was just going to be this acrimonious and useless kind of thing at the time. And I think Nick kind of got that a little bit. And it was weird. I had not spoken to Fuentes in quite some time. So they're both charming when they want to be, right? They didn't get to where they are by not being charming.  You know, there's a certain public persona. There's a persona you might have with your parents, say. There's a persona you have with your child. There's a persona you have at work. There's a persona you have when you're watching a football game or something. But so we all... And that's so important, right? We don't have just like this set personality. There are certain traits where we're outgoing or we're tough or we're vicious or we're ultra competitive, right? These so-called, you know, essential character traits that we have, right? They are domain specific. They're situation specific. We all adopt different personas in different parts of life. Put on a mask, I'm sorry, of course. But, you know, I've heard this about Fuentes. And I heard this from other people. Even people who dislike him intensely. But that is that if you ever can kind of get him off the online debate stage, he can actually be reasonable. And he is intelligent. But he can actually be thoughtful and reasonable and listen to you. And I have to say, I talked with him, I don't know, maybe it was 30 minutes, something like that. It wasn't a huge thing. But I have to handle what Fuentes does. Now, granted, perhaps I'm going to change my mind immediately when he starts doing his usual tricks afterward. But the guy was, he's very reasonable. He's more self-aware than he lets on. I mean, I think one thing that we both... Okay, we all get in situations where we have to change our personalities, whether it's work or we're playing football or in some sort of contest. So this shouldn't be nearly as surprising as it seems to be for Richard. You know, of course he can be intelligent and charming. Of course he switches in and out of different personas we all do. All notice is that kind of weird manic persona where he's the only guy on screen and he is playing this kind of weird zoomer gamer slash mid-western talk radio host, slash video game playing edge lord.  Okay, good, fine, you got to get out, you got to get out. All right, what do we think? You know, there's a certain kind of mannerism and there's a lot of picking up on Trumpism. The use of we is something, there's actually a study in which leaders actually use I more than we, but with Trump it's we. So it's a, you were part of a collective through me in a way. Like, you know... So pundits become successful by feeding an audience. Now by challenging an audience, like Richard wants to develop an audience that wants to be challenged, but there's no money in that. There's no money in being right in your punditry. The money is in being interesting and in feeding an audience's desire to hear reasons for why what they believe and feel is true and good and better than the alternative. He's behind us all the way. We hate Mitch McConnell, he's right okay. It's not a royal we, it's actually kind of a presumed we where you have political consciousness through an individual. He does that, but it's funny. Maybe it was just a fact that he was actually kind of relaxed and I was not hacking him and it was actually good conversation. I think behind all of that craziness, there is someone who's actually intelligent and I think maybe that's a little bit tragic about Nick. But the main thing I told him was, you know, do you feel like you are being used? That was effectively what I asked him. It was a leading question because obviously my assumption is that the answer is yes. And what I was referring to is like, you have these conservative institutions, the women for Trump say that created the... Of course he's being used. We're all being used, right? We're all being used and we're all using other people. So this isn't some giant revelation, right? We all try to use other people to meet our needs. Other people try to use us to meet their needs, of course. They rented out the ellipse actually during January 6th and the whole apparatus, behind the scenes apparatus, of Ali Alexander and Roger Stone and all of these crazies and George and so on.  They have an institution and so they have like a massive email list. They have a network. So yeah, of course he's being used. That shouldn't be so surprising, right? People just don't do nice things for as purely out of the goodness of their hearts, right? There are a whole lot of transactions going on. We're all using and being used. That's just the nature of reality, right? Your boss doesn't give you a paycheck just out of the goodness of his heart. He gives you a paycheck in exchange for services. Husbands and wives constantly doing things for each other. The man takes out the trash, the woman cleans the bathroom and the man may bring home the majority of the income. Much of life is transactional. You can be subtler or you can be more obvious with it. That's the nature of reality. That's how the world works. You know what? I'm coming back here a thousand times if I have to. We win. They lose. That's how the world works.


Hello, you're watching The International Daily Roundup by People's Dispatch, where we bring you some of the top stories from around the world. Let's take a look at today's headlines. Nepal ratifies controversial $500 million U.S. grant. African migrants face racism at Ukraine, Poland, water. 33 Colombian social leaders killed in 2022. And Sudan's resistance committees present political charter. In our first story, Nepal's parliament has ratified a controversial $500 million grant by the United States. The country has signed the U.S. government's Millennium Challenge Corporation, or MCC, packed in 2017. The deal's stated purpose was to provide funds for infrastructure projects, including power transmission lines and roads. The packed, sparked protests in Nepal, which were met with heavy repression. Communist parties within Prime Minister Duba's ruling coalition rejected the packed, arguing that it would undermine Nepal's sovereignty. La Via Campesina also condemned the packed as an instrument of new types of imperialism to pursue economic hegemony. It added that the packed would threaten food sovereignty, self-determination, political freedom and peace. Experts have argued that it is part of America's Indo-Pacific strategy. They have pointed to MCC's links to the U.S. military and the possibility of the entry of troops in Nepal. Local media reported that U.S. Assistant Secretary of State Donald Lu had urged Nepali politicians to endorse the packed by February 28. If not, Lu said that U.S. would review its ties with Nepal. The MCC packed was finally ratified after a compromise with the Communist Party of Nepal Maoist Center and the CPN Unified Socialist and the GSP. The grant agreement now includes an interpretative declaration which stipulates that Nepal will not become a part of any strategic military or security alliance with the United States, including the Indo-Pacific strategy. In our next story, the United Nations Refugee Agency has stated that more than 500,000 people have fled since the start of the war in Ukraine. The agency's head, Filippo Grande, added that the number could reach up to 5 million. The announcement came as officials from Russia and Ukraine arrived in Belarus to meet for crucial negotiations. More than 115,000 refugees, most of whom are women and children, have already crossed the border into Poland. Ukraine closed its airspace to civilian flights, forcing many to walk on foot to reach the border. However, African and other non-white migrants trying to flee to safety have described racism and discrimination at the border. Ukrainian police and border forces have reportedly blocked migrants from boarding trains and even pointed guns at them. A man told the Independent that he is his family and several other people were ordered to disembark from the bus after being told no blacks. People who have been left stranded have taken to social media to share the testimonies. 24 Jamaican students who arrived in Lviv from Kharkiv on Saturday were forced to walk 24 km to Poland on Sunday.  A student, Enzay, also shared footage on social media which appeared to show Ukrainian forces threatening to shoot people. He also said that some African migrants had been waiting at the border for two days. People have been stranded without food and water in extremely cold weather. Next we go to Colombia, which has recorded the deaths of at least 33 social leaders in 2022 so far. The Indepas confirmed the death of Gustavo Antonio Torres on February 26. He was shot and killed by armed men in his home in the Tibu municipality. Torres had been forcibly displaced after the formation of the Kanyo-India Productivo Association. The Ombudsman's Office had already issued an alert on the presence of illegal armed groups which social leaders classified as military objectives. Torres was killed a day after the murder of an indigenous guard and leader Dilsin Borja-Domiko in Antiochia. He was killed in Turbo, which reportedly has the highest concentration of drug-related insecurity. The local community is also at a high risk of violence. Colombia was also rocked by the murders of two prominent peasant leaders last week. Tiofilo Acunia and Jorge Tafur were killed in the municipality of San Martín on February 22. Both had been members of the National Agrarian Coordinator or CNA and the People's Congress and fought for the recovery of land. They had also condemned the San Martín police and mayor for harassing victims of violence in the community. Members of the People's Congress have been increasingly targeted with threats and violence in their struggle for peace and human rights. In Depal's has estimated that 1319 social leaders have been assassinated since the beginning of the peace accords in 2016. And finally, thousands of elderly people in Sudan held a Mothers and Fathers march on February 26. The protest was held in support of the youth who have mobilized under resistance committees against the Junta. Marches were held in the capital city as well as in states including Jazeera, Blue Nile and North Codofan. At least 83 protesters have been killed and over 3,000 have been injured since the October coup. Chanting, our children are not alone, we stand with them, protesters marched in Khartoum on Saturday. At least 34 people were injured after security forces cracked down on the crowds. On February 27, the Khartoum state resistance committees presented a proposal for the charter for the establishment of the People's Authority. It reiterates the rejection of negotiations with the military and the continuation of peaceful resistance. The text calls for the cancellation of the 2019 constitutional document and a review of all agreements since April 11 that year. It lays out a two-year transition under Prime Minister chosen by the charter's signatory. The text also proposes transitional governance structures based on a federal system. It includes mechanisms to prosecute those involved in rights violation and war crimes in 2019 and the crimes committed since the coup. The charter also includes proposals for lasting peace, the economy and development and foreign relations. It also includes reforms for the judicial system, the civil services and the military. The text also calls for a constitution-making national commission and popular participation in the drafting process. And that's all for today's episode. For more such stories, visit our website at peoplesdispatch.org and follow us on Facebook, Twitter and Instagram. Thank you for watching.