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Hello, everyone.

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So in this lesson, we will discuss the ways to implement our priorities.

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But before starting the topic, let us discuss what is practical and let us revise what is exploding

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you.

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So suppose these are my elements.

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So Minecraft, Casey's first main element will come the element.

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Having the least Baradi will come first.

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So first, when will come?

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Then Elemental will come.

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And let's say now I'm inserting the element 20.

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So elementally welcome.

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Now, let's say I am again inserting the element zero.

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So now this time zero will welcome.

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Because zero has the least priority now, let us consider this example makes it a priority to eliminate

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having them exempt.

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They will come first.

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So first 14, welcome.

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Then I will come, then let's say I'm inserting 20, so then they will come now let's say I'm starting

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zero, then element it will come.

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So in this way, the element having the mix priority are coming out first and in the minimum priority,

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the element having the least priority will come first.

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Simple.

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Now let us discuss the ways to implement triadic you.

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So as discussed in the last video, we need to function, we need insert function, we need to get the

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minimum function in case of you, we need to get the maximum function in case of make simpler dequeue

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and similarly remove minimum and remove maximum function.

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So the first year, the structure that we can use for implementing protocol is Eddie.

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Now, Eddie can be of two types.

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First, let's discuss about unsorted Eddie.

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So in case of unsorted Eddie.

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Here, I will read the -- complexities over the time, complexity for session, so since the phrase

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unsorted so you can insert the element at the last time, complexities, constant big ofman.

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Now the Eddison ordered and you want to find out the minimum or the maximum limit.

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So what you have to do, you have to perform the edit reversal to find out the minimum or make some

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element because our arrays unsorted.

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So the time complexities big often.

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Now, third function, remove minimum or remove him, so here you will need two drivers.

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So first, drivers basically.

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We will try to find out the minimum or the maximum limit and then what they have to do, so basically

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we have to shift all of that elements.

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So in this case, so suppose this is my area now you want to remove this element.

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So for removing this element, you have to shift this area.

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The words left by one unit, so.

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First big event to find out the meaning of the Maksym element, and then you have to shift all the other

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elements.

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So in the worst case, you have to shift end elements.

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So, again, the time complexities, doing and doing is actually big often.

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So I insert will work perfectly fine, but these two are very expensive, big often and big often.

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Now let's discuss our security structure so that we can use we can use our edit instead of edit artillery,

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OK, we can use this already.

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So in case of minimum priority, our address will be sorted in ascending order.

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In case of mixing particular, our area will be sorted in descending order.

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Simple.

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Now, let us discuss the time complexity now you want to insert an element.

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So since the area started, so first, what do you have to do?

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You have to find out the correct position for the element to be inserted and then you will insert the

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element and you have to shift all the other elements of the.

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So, again, and placenta's actually big often.

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Now you want to find out the minimum or the maximum limit.

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So, again, minimum or the maximum will be present at the first index.

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So it will be question time.

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And if you want to remove minimum element, so we know the minimum element is present at the first index

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or the maximum limit, especially the first NICS.

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And then basically you have to shift the area.

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You have to shift all of the elements.

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So Konstantine plus linear time.

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So it is big often.

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Now, in this case, I will get the minimum, get maximum function is performing really good, but instead

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function as expensive.

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Similarly, remove minimum and maximum function is also expensive.

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Now let's discuss the target, the structure that we have.

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So we have linked lists.

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Now first, let's discuss about unsorted linked list.

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So unsorted means we do not consider we do not care about the order in which the elements are present.

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So first, let's discuss about the insert function, so there are two ways you can insert that head

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or you can insert detail.

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So if you are inserting it had the time, complexity is big often, and if you're inserting a little

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material, you will maintain a little pointer.

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So inserting a tail is also a big government.

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Now get me nor get the maximum.

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So finding out, get the minimum or you for finding out the minimum, the maximum element.

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But you have to do you have to traverse the complete length list because I will include this unsorted

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so time complexities again big often now four remove minimum and remove maximum function.

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First you have to find that element.

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So basically you have to perform the traversal now for removing.

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So EnLink list removal is on.

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So time complexities big often now and linked list in third function is very good, but get the minimum

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and remove many more to make them function is expensive.

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Now, the fourth traders actually can use is basically a long list sorted.

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So inserted link list, again, if I'm implementing minimum priority queue, our linked list will be

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sorted in ascending order, otherwise it will be sorted in descending order for the maximum variety.

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You know, let us discuss first insert function.

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Now, what do you have to do so first of all, you have to find out the correct position at which you

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have to searched so for finding out the correct position, you have to add to the list.

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And then basically the insertion is question time.

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So, again, the time complexities big often for finding out the M.O., the MAKSYM element.

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So since the Linklaters started, so minimum or the maximum element will be at head only.

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So again, question time now for removing the minimum, the maximum element.

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So for removing we know the maximum or the minimum element will represent dopehead.

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So over time and finding out the minimum element and then again over time for removal.

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So time complexities, big one.

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Now these two functions are performing really, really good, but is function is expensive.

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Now, the next to the structure that we can discuss is let's discuss about Best Baynie surgery so we

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know what is a by necessity.

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So all the left values are smaller than the root.

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All the right values are good and simple.

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Now, if you want to insert in a body safwat insertion in the time complexities, big of Etch Sketch

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is the height of the tree in worst case.

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It will be big off and the worst case and the worst case I would hide will be in so far and complexity

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will be big, Wolf.

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And.

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Now let's discuss about get minimum or get mixed maximum function, so if you want to find out the minimum

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element in what you have to do, you will go left, left, left, left, left.

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So extreme left will have to go extreme left.

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So order of age for finding out the maximum element.

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So maximum will be present at the extreme right.

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So you will go.

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Right, right, right, right, right.

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So time complexities big of each.

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Now, again, in the worst case, it will be big off and.

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For the movement, functionality will make him function again, the time complexity will be of which

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simple in the worst case, again, it will be big.

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Often in the worst case, it will be big often.

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So now let's discuss our next new structure.

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So what we can use, we can use a balance to be bisdee.

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Instead of using normal bisdee, we will use balanced bisdee.

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So what is a balanced body?

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So the difference between the left and the right substrate.

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So this is more or less so difference between the left and the right supplicate will be denoted close

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to one.

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Now in the balance to be used again, but over time, complexity for In Session Big off edge and we

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can assume so.

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This is Logan.

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Because we have balanced obviously so high, it will always be Logan, so again, get a minimum or get

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maximum function time complexities.

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Begovic and height is always Logan.

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And this case also our is always log-in.

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So big off, big off logging now all three functions are medullary, they are neither good nor expensive.

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So now let us compare all these data.

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So suppose I have inquiries.

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Now, in these inquiries, what I have to do, I have to insert names so you will insert and times and

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you will remove any names, so names in association and names removal.

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So now let us try to discuss the time complexity for each investigator.

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So first of all, let us discuss about unsorted Eddie.

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So you are inserting and time constraint time, but for removing it will take and time and data and

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elements of time, complexities and squit again.

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So avoiding section and square time again and square and square is simple and square.

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For unsorted, long list in session is constant name, but.

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Any movement you want to make, some it will take and it's a good time because for one element it will

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take time and we have an element.

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So it's great again for Citilink List.

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So this is and square and this is constant.

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So Anscar time for the best and the worst case.

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This is this will be the time complexity of organization and this will be 40 remould.

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So again the time complexity will be squared plus and square, so simple and square.

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Now let us discuss about the balanced body.

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So this will be and Logan Glass and Logan so and Logan percent.

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Logan two and Logan so simply.

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And Logan.

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So if you will compare, this is performing the best.

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This is giving me the best performance and Logan arrest and really the structures giving me and square.

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Now, you can think of one as a picture, so we can also use an order to map.

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So in another map, what is their time, complexity for inception, so time complexity is constant.

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Now get them in order to make them function, but they have to do you have to traverse over the complete

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map so for traversal it will take a lot of time.

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And similarly, if you want to remove the minimum, the maximum limit, you first have to find out the

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minimum element and for finding out the minimum element.

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First, you have to perform the traversal and the removal is constant.

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So again, it is Magoffin and modular time complexity.

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So this constant insertion is constant, but you have to in certain elements and for one element it

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will take and time.

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So time, complexities and square.

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Now again, if you will compare, balanced bisdee gives us the best performance and.

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And so this is best.

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So in the next video, we will discuss how we can implement our own priorities.

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You I will assume the next one, but by.