by: Maple

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You can find more information and an application form at Maple Ambassador Program. We’re looking forward to hearing from you!

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Maple Product Management

## Finding an approximate function for a PDE numerica...

Are there any commands in maple that will help me find a suitable function that approximates the numerical solution of:

 > restart;   PDE := diff(v(x, t), t) = diff(v(x, t), x, x);   JACOBIINTEGRAL := int(JacobiTheta3(0, exp(-Pi^2*s))*v(1, t-s)^4, s = 0 .. t);   IBC:= D[1](v)(0,t)=0,         D[1](v)(1,t)=-0.000065*v(1, t)^4,         v(x,0)=1; # # For x=0..1, t=0..1, the solution varies only very slowly # so I have increased the timestep/spacestep, just to speed # up results generation for diagnostic purposes #   pds := pdsolve( PDE, [IBC], numeric, time = t, range = 0 .. 1,                   spacestep = 0.1e-1, timestep = 0.1e-1,                   errorest=true                 )
 (1)
 > # # Plot the solution over the ranges x=0..1, # time=0..1. Not a lot happens! #   pds:-plot(x=1, t=0..1);
 > # # Plot the estimated error over the ranges x=0..1, # time=0..1 #   pds:-plot( err(v(x,t)), x=1,t=0..1);
 > # # Get some numerical solution values #   pVal:=pds:-value(v(x,t), output=procedurelist):   for k from 0 by 0.1 to 1 do       pVal(1, k)[2], pVal(1, k)[3];   od;
 >
 (2)
 >
 >

I am refering to the first graph, is there a way in maple to find an explicit suitable approximating function?

I.e, I want the function to have the same first graph obviously, it seems like addition of exponent and a line function, I tried plotting exp(-t)-0.3*t, it doesn't look like it approximates it very well. Any suggestion on how to implement this task in maple?

Thanks.

## Convergence problem for some values of parameters...

Dear collagues

Hi,

I write a code to solve a system of ODE. It solve the ODES in a wide range of parameters but as I decrease NBT below 0.5, it doesnt converge. I do my best but I couldn't find the answer. Would you please help me? Thank you

Here is my code and it should be run for 0.1<NBT<10. the value of NBT is input directly in res1.

restart:
EPSILONE:=1000:
Digits:=15:

a[mu1]:=5.45:
b[mu1]:=108.2:
a[k1]:=1.292:
b[k1]:=-11.99:

rhop:=4175:
rhobf:=998.2:
mu1[bf]:=9.93/10000:
k1[bf]:=0.597:

rhost(eta):=1-phi(eta)+phi(eta)*rhop/rhobf;
k:=unapply(k1[bf]*(1+a[k1]*phi(eta)+b[k1]*phi(eta)^2),eta);

eq1:=(diff(u(eta), eta))*a[mu1]*(diff(phi(eta), eta))+2*(diff(u(eta), eta))*b[mu1]*phi(eta)*(diff(phi(eta), eta))+((diff(u(eta), eta))+(diff(u(eta), eta))*a[mu1]*phi(eta)+(diff(u(eta), eta))*b[mu1]*phi(eta)^2)/(eta+EPSILONE)+diff(u(eta), eta, eta)+(diff(u(eta), eta, eta))*a[mu1]*phi(eta)+(diff(u(eta), eta, eta))*b[mu1]*phi(eta)^2+1-phi(eta)+phi(eta)*rhop/rhobf:
eq2:=(1+a[k1]*phi(eta)+b[k1]*phi(eta)^2)*(diff(T(eta), eta))/(eta+EPSILONE) + (a[k1]*(diff(phi(eta), eta))+2*b[k1]*phi(eta)*(diff(phi(eta), eta)))*(diff(T(eta), eta))+(1+a[k1]*phi(eta)+b[k1]*phi(eta)^2)*(diff(T(eta), eta, eta));
eq3:=diff(phi(eta),eta)+phi(eta)/(N_bt*(1+gama1*T(eta))^2)*diff(T(eta),eta):

eq2:=subs(phi(0)=phi0,eq2):
eq3:=subs(phi(0)=phi0,eq3):

eval(dsolve({eq3,phi(1)=phiv},phi(eta)),(T)(1)=1):
Phi:=normal(combine(%)):
Teq:=isolate(eval(eq2,Phi),diff(T(eta),eta)):
ueq1:=eval(eq1,Phi)=0:
ueq2:=subs(Teq,ueq1):

lambda:=0;
Ha:=0;
N_bt:=cc*NBT+(1-cc)*0.8;
kratio:=k1[p]/k1[bf]:

GUESS:=[T(eta) =0.0001*eta, u(eta) =0.1*eta, phi(eta) = 0.3*(eta-1)^4];
res1 := dsolve(subs(NBT=0.48,gama1=0.2,phiv=0.06,{eq1,eq2,eq3,u(0)=lambda*D(u)(0),D(u)(1)=0,T(0)=0,phi(1)=phiv,T(1)=1}), numeric,method=bvp[midrich],maxmesh=4000,approxsoln=GUESS, output=listprocedure,continuation=cc):
G0,G1,G2:=op(subs(subs(res1),[phi(eta),u(eta),diff(T(eta),eta)])):

masst:=evalf(int((1-G0(eta)+G0(eta)*rhop/rhobf)*G1(eta), eta = 0..1));
heatt:=(1+a[k1]*G0(0)+b[k1]*G0(0)^2)*G2(0);

plots:-odeplot(res1,[[eta,T(eta)]],0..1,legend=[T],color=["Black"],linestyle=Solid,axes=boxed,thickness=3);
plots:-odeplot(res1,[[eta,u(eta)]],0..1,legend=[u],color=["Black"],linestyle=Solid,axes=boxed,thickness=3);
plots:-odeplot(res1,[[eta,phi(eta)]],0..1,legend=[phi],color=["Black"],linestyle=Solid,axes=boxed,thickness=3);

>
>

Thank you

Amir

## Plotting 3 planes and the intersection point...

Hello all

I am trying to write  a tutorial about systems of linear equations, and I want to demonstrate the idea that when you have a system of 3 euqtions with 3 unknowns, the solution is the intersection point between these planes. Plotting 3 planes in Maple 2015 is fairly easy (you plot one and just drag the others in), but I don't know how to plot the intersection point. Can you help please ?

My equations are:

x-2y+z=0

2y-8z=8

-4x+5y+9z=-9

The intersection point is (29,16,3)

Thank you !

## Analytic solution of dsolve...

Dear Collegues

I have a system of odes as follows

restart:
#gama1:=0.2:

#rhop:=5180:
#rhobf:=998.2:
#a[mu1]:=39.11:
#b[mu1]:=533.9:
#a[k1]:=7.47:
#b[k1]:=0:

Teq := N_bt*T(eta)^2*(exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta)))))^2*(diff(T(eta), eta, eta))*gama1^2*b[k1]+N_bt*T(eta)^2*exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta))))*(diff(T(eta), eta, eta))*gama1^2*a[k1]+2*N_bt*T(eta)*(exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta)))))^2*(diff(T(eta), eta, eta))*gama1*b[k1]+N_bt*T(eta)^2*(diff(T(eta), eta, eta))*gama1^2;

UEQ:=(a[mu1]*(-(diff(T(eta), eta))/(N_bt*(1+gama1)*(1+gama1*T(eta)))+(T(eta)-1)*gama1*(diff(T(eta), eta))/(N_bt*(1+gama1)*(1+gama1*T(eta))^2))*exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta))))+2*b[mu1]*(exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta)))))^2*(-(diff(T(eta), eta))/(N_bt*(1+gama1)*(1+gama1*T(eta)))+(T(eta)-1)*gama1*(diff(T(eta), eta))/(N_bt*(1+gama1)*(1+gama1*T(eta))^2)))*(diff(u(eta), eta))+(1+a[mu1]*exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta))))+b[mu1]*(exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta)))))^2)*(diff(u(eta), eta, eta))+1-exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta))))+exp(-(T(eta)-1)/(N_bt*(1+gama1)*(1+gama1*T(eta))))*rhop/rhobf;

I want to solve them with the following boundary conditions

T(0)=0, T(1)=1

u(0)=L*D(u)(0), D(u)(1)=0

However I tried, I cannot find the solution in a closed form. I want to know that is there a closed form solution for the above odes?

Thank you

Amir

## Exact solutions to Einstein's equations

by:

Exact solutions to Einstein’s equations” is one of those books that are difficult even to imagine: the authors reviewed more than 4,000 papers containing solutions to Einstein’s equations in the general relativity literature, collecting, classifying, discarding repetitions in disguise, and organizing the whole material into chapters according to the physical properties of these solutions. The book is already in its second edition and it is a monumental piece of work.

As good as it is, however, the project resulted only in printed material, a textbook constituted of paper and ink. In 2006, when the DifferentialGeometry package was rewritten to enter the Maple library, one of the first things that passed through our minds was to bring the whole of “Exact solutions to Einstein’s equations” into Maple.

It took some time to start but in 2010, for Maple 14, we featured the first 26 solutions from this book. In Maple 15 this number jumped to 61. For Maple 17 we decided to emphasize the general relativity functionality of the DifferentialGeometry package, and Maple 18 added 50 more, featuring in total 225 of these solutions - great! but still far from the whole thing …

And this is when we decided to “step on the gas” - go for it, the whole book. One year later, working in collaboration with Denitsa Staicova from Bulgarian Academy of Sciences, Maple 2015 appeared with 330 solutions to Einstein’s equations. Today we have already implemented 492 solutions, and for the first time we can see the end of the tunnel: we are targeting finishing the whole book by the end of this year.

Wow2! This is a terrific result. First, because these solutions are key in the area of general relativity, and at this point what we have in Maple is already the most thorough digitized database of solutions to Einstein’s equations in the world. Second, and not any less important, because within Maple this knowledge comes alive. The solutions are fully searcheable and are set by a simple call to the Physics:-g_  spacetime metric command, and that automatically sets the related coordinates, Christoffel symbols , Ricci  and Riemann  tensors, orthonormal and null tetrads , etc. All of this happens on the fly, and all the mathematics within the Maple library are ready to work with these solutions. Having everything come alive completely changes the game. The ability to search the database according to the physical properties of the solutions, their classification, or just by parts of keywords also makes the whole book concretely more useful.

And, not only are these solutions to Einstein’s equations brought to life in a full-featured way through the Physics  package: they can also be reached through the DifferentialGeometry:-Library:-MetricSearch  applet. Almost all of the mathematical operations one can perform on them are also implemented as commands in DifferentialGeometry .

Finally, in the Maple PDEtools package , we already have all the mathematical tools to start resolving the equivalence problem around these solutions. That is: to answer whether a new solution is or not new, or whether it can be obtained from an existing solution by transformations of coordinates of different kinds. And we are going for it.

What follows is a basic illustration of what has already been implemented. As usual, in order to reproduce these results, you need to update your Physics library from the Maplesoft R&D Physics webpage.

Load Physics , set the metric to  (and everything else automatically) in one go

 >
 >
 (1)

And that is all we do :) Although the strength in Physics  is to compute with tensors using indicial notation, all of the tensor components and related properties of this metric are also derived on the fly (and no, they are not in any database). For instance these are the definition in terms of Christoffel symbols , and the covariant components of the Ricci tensor

 >
 (2)
 >
 (3)

These are the 16 Riemann invariants  for Schwarzschild solution, using the formulas by Carminati and McLenaghan

 >
 (4)

The related Weyl scalars  in the context of the Newman-Penrose formalism

 >
 (5)

These are the 2x2 matrix components of the Christoffel symbols of the second kind (that describe, in coordinates, the effects of parallel transport in curved surfaces), when the first of its three indices is equal to 1

 >
 (6)

In Physics, the Christoffel symbols of the first kind are represented by the same object (not two commands) just by taking the first index covariant, as we do when computing with paper and pencil

 >
 (7)

One could query the database, directly from the spacetime metrics, about the solutions (metrics) to Einstein's equations related to Levi-Civita, the Italian mathematician

 >
 (8)

These solutions can be set in one go from the metrics command, just by indicating the number with which it appears in "Exact Solutions to Einstein's Equations"

 >
 (9)

Automatically, everything gets set accordingly; these are the contravariant components of the related Ricci tensor

 >
 (10)

One works with the Newman-Penrose formalism frequently using tetrads (local system of references); the Physics subpackage for this is Tetrads

 >
 (11)

This is the tetrad related to the book's metric with number 12.16.1

 >
 (12)

One can check these directly; for instance this is the definition of the tetrad, where the right-hand side is the tetrad metric

 >
 (13)

This shows that, for the components given by (12), the definition holds

 >
 (14)

One frequently works with a different signature and null tetrads; set that, and everything gets automatically recomputed for the metric 12.16.1 accordingly

 >
 (15)
 >
 (16)
 >
 (17)
 >
 (18)

The related 16 Riemann invariant

 >
 (19)

The ability to query rapidly, set things in one go, change everything again etc. are at this point fantastic. For instance, these are the metrics by Kaigorodov; next are those published in 1962

 >
 (20)
 >
 (21)

The search can be done visually, by properties; this is the only solution in the database that is a Pure Ratiation solution, of Petrov Type "D", Plebanski-Petrov Type "O" and that has Isometry Dimension equal to 1:

 >

Set the solution, and everything related to work with it, in one go

 >
 (22)

The related Riemann invariants:

 >
 (23)

To conclude, how many solutions from the book have we already implemented?

 >
 (24)
 >
 (25)
 >

:)

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

## Multiple plot with DiscretePlot?...

with(DynamicSystems)

T:= a vector

Iwant to make a single plot of:

DiscretePlot(T,x1,stile=stair); DisdretPlot(T,x2,stile=stair)

The usal way: DiscreePlot(T,[x1,x2]... ain't work

Thansk for helping

## New: Factorizing with non-commutative variables

by:

One of the interesting things about the Physics package is that it was designed from scratch to extend the domain of operations of the Maple system from commutative variables to one that includes commutative, anticommutative and nonocommutative variables, as well as abstract vectors and related (nabla) differential operators. In this line we have, among others, the following Physics commands working with this extended domain: `*` , `.` , `^` , diff , Expand , Normal , Simplify , Gtaylor , and Coefficients .

More recently, Pascal Szriftgiser (from Laboratoire PhLAM, Université Lille 1, France), suggested a similar approach to factorize expressions involving noncommutative variables. This is a pretty complicated problem though. Pascal's suggestion, however, spinned around an idea beautiful for its simplicity, similar to what is done in the experimental Physics command, PerformOnAnticommutativeSystem , that is, to transform the problem into one that can be treated with the command that works only with commutative variables and from there extract the result for noncommutative ones.The approach has limitations but it is surprising how far one can go using imaginative algebraic manipulations to extend these commands that otherwise only work with commutative variables.

In brief, we now have a new command, Physics:-Factor, with already powerful performance for factorizing algebraic expressions that involve commutative, noncommutative and anticommutative variables, making Maple's mathematical capabilities more advanced in very interesting directions. This command is in fact useful not just in advanced theoretical physics, but for instance also when working with noncommutative symbols representing abstract matrices (that can have dependency, and so they can be differentiated before saying anything about their components, multiplied, and be present int  expressions that in turn can be expanded, simplified and now also factorized), and also useful with expressions that include differential operators, now that within Physics you can compute with the the covariant and noncovariant derivatives D_  and d_ algebraically. For instance, how about solving differential equations using Physics:-Factor (reducing their order by means of factoring the involved differential operators) ? :)

What follows are some basic algebraic examples illustrating the novelty, and as usual to reproduce the results in this worksheet you need to update your Physics library with the one available in the Maplesoft R&D Physics webpage.

 >
 (1)
 >
 (2)

First example, because of using mathematical notation, noncommutative variables are displayed in different color (olive)

 >
 (3)
 >
 (4)

A more involved example from a physics problem, illustrating that the factorization is also happening within function's arguments, as well as that we can also correctly expand mathematical expressions involving noncommutative variables

 >
 (5)
 >
 (6)

So first expand ...

 >
 (7)

Now retrieve the original expression by recursing over the arguments and so factoring the integrand

 >
 (8)

This following one looks simpler but it is actually more complicated:

 >
 (9)
 >
 (10)

The complication consists of the fact that the standard factor  command, that assumes products are commutative, can never deal with factors like  because if products were commutative these factors are equal to 0. Of course we not just us factor but include a number of algebraic manipulations before using it, so that the approach handles these cases nicely anyway

 >
 (11)

This other one is more complicated:

 >
 (12)

When you expand,

 >
 (13)

you see that there are various terms involving the same noncommutative operands, just multiplied in different order. Generally speaking the limitation (n this moment) of the approach is: "there cannot be more than 2 terms in the expanded form containing the same operands" . For instance in (13) the 1st and 4th terms have the same operands, that are actually also present in the 5th term but there you also have  and for that reason (involving some additional manipulations) it can be handled:

 >
 (14)

Recalling, in all these examples, the task is actually accomplished by the standard factor  command, and the manipulations consist of ingeniously rewriting the given problem as one that involves only commutative variables, and from extract the correct result for non commutative variables.

To conclude, here is an example where the approach implemented does not work (yet) because of the limitation mentioned in the previous paragraph:

 >
 (15)
 >
 (16)

In this expression, the 1st, 2nd, 4th and 5th terms have the same operands  and then there are four terms containing the operands . We do have an idea of how this could be done too ... :) To be there in one of the next Physics updates.

 >

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

## Generating pairs in a sequence...

I wish to generate a sequence like
a[1], b[1], a[2], b[2], a[3], b[3]

The following does not work for the obvious reason:

seq(a[i], b[i], i=1..3);

What is the right way?

## How to use matrix symbol directly in equation deri...

Hi, I hope to use symbol A, B, directly to get C derivation, without using elements forms of matrix, as shown below.

How to achieve this?

Thank you.

## Nth order derivatives and Faa di Bruno formula

by:

In connection with recent developments for symbolic sequences, a number of improvements were implemented regarding symbolic differentiation, that is the computation of  order derivatives were n is a symbol, the simplest example being the  derivative of the exponential, which of course is the exponential itself. This post is about these developments, done in collaboration with Katherina von Bülow, and available for download as usual from the Maplesoft R&D web page for Differential Equations and Mathematical functions (the update itself is bundled with the official updates of the Maple Physics package).

It is important to note that Maple is pioneer in having an actual implementation of symbolic differentiation, something that works for real, since several releases.  The development, however, was somewhat stuck because we were unable to compute the symbolic  derivative of a composite function . A formula for this problem is actually known, it is the Faà di Bruno formula, but, in order to implement it, first we were missing the incomplete Bell functions , that got implemented in Maple 15, nice, but then we were still missing differentiating symbolic sequences, and functions whose arguments are symbolic sequences (i.e. the number of arguments of the function is n, a symbol, of unknown value at the time of differentiating). All this got implemented now within the new MathematicalFunctions:-Sequence package, opening the door widely to these improvements in  differentiation.

The symbolic differentiation code works as mostly all other computer algebra code, by mapping complicated problems into a composition of simpler problems all of which are tractable; what follows is then an illustration of these basic cases.

Among the simplest new case that can now be handled there is that of a power where the exponent is linear in the differentiation variable. This is actually an easy problem

 >
 (1)

More complicated, consider the  power of a generic function; the corresponding symbolic derivative can be mapped into a sum of symbolic derivatives of powers of  with lower degree

 >
 (2)

In some cases where  is a known function, the computation can be carried on furthermore. For example, for  the result can be expressed using Stirling numbers of the first kind

 >
 (3)

The case of sin and cos are relatively simpler, but then assumptions on the exponent are required in order to proceed further ahead from (2), for example

 >
 (4)

The case of functions of arbitrary number of variables (typical situation where symbolic sequences are required) is now handled properly. This is the pFq hypergeometric function of symbolic order p and q

 >
 (5)

The case of the MeijerG function is more complicated, but in practice, for the computer, once it knows how to handle symbolic sequences, the more involved problem becomes computable

 >
 (6)

Not only the mathematics of this result is correct: the object returned is actually computable to the end (if you provide the values of n, p, m and q), and the typesetting is actually fully readable, as in textbooks, including copy and paste working properly; all this is new.

The  derivative of a number of mathematical functions that were not implemented before, are now also implemented, covering the gaps, for example:

 >
 (7)
 >
 (8)
 >
 (9)
 >
 (10)

In the same way the fundamental formulas for the  derivative of all the 12 elliptic Jacobi functions  as well as the four elliptic JacobiTheta functions,  the LambertW , LegendreP  and some others are now all implemented.

Finally there is the "holy grail" of this problem: the  derivative of a composite function  - this always-unreachable implementation of Faa di Bruno formula. We now have it :)

 >
 (11)

Note the symbolic sequence of symbolic order derivatives of lower degree, both of of f and g, also within the arguments of the IncompleteBellB function. This is a very abstract formula ... And does this really work? Of course it does :). Consider, for instance, a case where the  derivatives of  and  can both be computed by the system:

 >
 (12)

This is the  derivative expressed using Faa di Bruno's formula, in turn expressed using symbolic sequences within the IncompleteBellB  function

 >
 (13)

These results can all be verified. Take for instance

 >
 (14)

Compute now the inert functions: on the left-hand side this is just the (now explicit) 3rd order derivative, while on the right-hand side we have a sum of IncompleteBellB  functions, where the number of arguments, expressed in (13) using symbolic sequences that depend on the summation index k and the differentiation order n, now in (14) depend only on , and get transformed into explicit sequences of arguments when the summation is performed and k assumes integer values

 >
 (15)

Take left-hand side minus right-hand side

 >
 (16)
 >

:)

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

## How to show chain rule when diff?...

how to show chain rules result when diff this

Eq1 := f(x,g(x,t)) + f(x,y);
diff(Eq1, x);

http://math.stackexchange.com/questions/372093/chain-rule-definition-f-fx-gx-y

## Tricky calculation for a simple equation...

The equation tan(y) = 2*tan(x) defines y implicitly as a function of x.  Well, perphas "defines" is too strong a word, since there are multiple solutions for y.  However, if I am not mistaken, there exists a unique continuous solution y(x) that goes through the origin, that is, y(0)=0, and is defined for all x.

Question 1: How do we plot the graph of y(x)?

I have a roundabout solution as follows.  Differentiate the equation tan(y(x)) = 2*tan(x) with respect to x and arrive at a first order differential equation in y(x).  Solve the differential equation with the initial condition y(0)=0.  Surprisingly, Maple obtains an explicit solution:

which we can plot:

plot(rhs(%), x=0..2*Pi);

Question 2: Is there a neat way of getting that solution with algebra only, without appealing to differential equations?

## Vector Analysis for Engineering: Using Maplesoft...

Maple 2015

In this work the theme of vector analysis shown from a computational point of view; this being a very important role in the engineering component; in civil and mechanical special it is why, using the scientific software Maple develops interactive solutions for long processes through MapleCloud calculations. At present the majority of professors / researchers perform static classes open source leaves; so that our students learn and memorize commands, thus generating more time learning in the area. Loading Bookseller VectorCalculus develop topics: vector algebra, differential operators, conservative fields, etc. Maplesoft making processes provide immediate calculations long operation Embedded Components displayed in line with MapleNet integrations. Today our future engineers to design solutions and will be launched in the cloud thus being a process with global qualification in the specialty. Significantly Maple is a scientific software which allows the researcher to design their own innovations and not use themes for their manufacturers.

III_CRF_2015.pdf

CRF_2015.mw

L.AraujoC.

## which one is right?...

In Maple 11 we have:

> A := <a,b,c>:
> a := 1:  b := 2: c := 3:
> convert(A, list);
[1, 2, 3]

In Maple 2015 we have:

> A := <a,b,c>:
> a := 1:  b := 2: c := 3:
> convert(A, list);
[a, b, c]

Is that change really intended?

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