ACV para árvore n-ária | Consulta Constante O(1)
Vimos vários métodos com diferentes complexidades de tempo para calcular LCA na árvore n-ária: -
Método 1: Método Naive (calculando o caminho da raiz ao nó) | O(n) por consulta
Método 2: Usando decomposição Sqrt | O (quadrado H)
Método 3: Usando abordagem Sparse Matrix DP | O(logn)
Vamos estudar outro método que possui tempo de consulta mais rápido do que todos os métodos acima. Portanto, nosso objetivo será calcular o LCA em tempo constante ~ O (1) . Vamos ver como podemos conseguir isso.
Método 4: usando consulta de intervalo mínimo
Nós discutimos LCA e RMQ para árvore binária . Aqui discutimos a conversão do problema LCA em problema RMQ para árvore n-ária.
Pre-requisites:- LCA in Binary Tree using RMQ RMQ using sparse table
Conceito-chave: Neste método estaremos reduzindo nosso problema de LCA para um problema de RMQ (Range Mínimo Query) em um array estático. Depois de fazer isso, relacionaremos as consultas mínimas do intervalo às consultas LCA necessárias.
O primeiro passo será decompor a árvore em uma matriz linear plana. Para fazer isso podemos aplicar o passeio de Euler. A caminhada de Euler fornecerá o percurso de pré-ordem do gráfico. Portanto, realizaremos um Euler Walk na árvore e armazenaremos os nós em um array à medida que os visitarmos. Este processo reduz a árvore > 
Agora vamos pensar em termos gerais: considere dois nós quaisquer na árvore. Haverá exatamente um caminho conectando ambos os nós e o nó que tiver o menor valor de profundidade no caminho será o LCA dos dois nós fornecidos.
Agora pegue quaisquer dois nós distintos, digamos em e v na matriz de caminhada de Euler. Agora, todos os elementos no caminho de u a v ficarão entre o índice dos nós u e v no array de caminhada de Euler. Portanto, precisamos apenas calcular o nó com a profundidade mínima entre o índice do nó u e do nó v no array euler.
Para isso manteremos outro array que conterá a profundidade de todos os nós correspondentes à sua posição no array Euler walk para que possamos aplicar nosso algoritmo RMQ nele.
Abaixo está o array euler walk paralelo ao seu array de profundidade.
Exemplo: - Considere dois nós nó 6 e nó 7 na matriz euler. Para calcular o LCA do nó 6 e do nó 7, procuramos o menor valor de profundidade para todos os nós entre o nó 6 e o nó 7.
Portanto nó 1 tem o menor valor de profundidade = 0 e, portanto, é o LCA para o nó 6 e o nó 7.
Implementação:-
We will be maintaining three arrays 1) Euler Path 2) Depth array 3) First Appearance Index
A matriz Euler Path e Depth são iguais às descritas acima
Índice de primeira aparição FAI[]: O First Appearance index Array armazenará o índice para a primeira posição de cada nó no array Euler Path. FAI[i] = Primeira aparição do i-ésimo nó no array Euler Walk.
A implementação do método acima é fornecida abaixo: -
Implementação:
C++ // C++ program to demonstrate LCA of n-ary tree // in constant time. #include 'bits/stdc++.h' using namespace std ; #define sz 101 vector < int > adj [ sz ]; // stores the tree vector < int > euler ; // tracks the eulerwalk vector < int > depthArr ; // depth for each node corresponding // to eulerwalk int FAI [ sz ]; // stores first appearance index of every node int level [ sz ]; // stores depth for all nodes in the tree int ptr ; // pointer to euler walk int dp [ sz ][ 18 ]; // sparse table int logn [ sz ]; // stores log values int p2 [ 20 ]; // stores power of 2 void buildSparseTable ( int n ) { // initializing sparse table memset ( dp -1 sizeof ( dp )); // filling base case values for ( int i = 1 ; i < n ; i ++ ) dp [ i -1 ][ 0 ] = ( depthArr [ i ] > depthArr [ i -1 ]) ? i -1 : i ; // dp to fill sparse table for ( int l = 1 ; l < 15 ; l ++ ) for ( int i = 0 ; i < n ; i ++ ) if ( dp [ i ][ l -1 ] != -1 and dp [ i + p2 [ l -1 ]][ l -1 ] != -1 ) dp [ i ][ l ] = ( depthArr [ dp [ i ][ l -1 ]] > depthArr [ dp [ i + p2 [ l -1 ]][ l -1 ]]) ? dp [ i + p2 [ l -1 ]][ l -1 ] : dp [ i ][ l -1 ]; else break ; } int query ( int l int r ) { int d = r - l ; int dx = logn [ d ]; if ( l == r ) return l ; if ( depthArr [ dp [ l ][ dx ]] > depthArr [ dp [ r - p2 [ dx ]][ dx ]]) return dp [ r - p2 [ dx ]][ dx ]; else return dp [ l ][ dx ]; } void preprocess () { // memorizing powers of 2 p2 [ 0 ] = 1 ; for ( int i = 1 ; i < 18 ; i ++ ) p2 [ i ] = p2 [ i -1 ] * 2 ; // memorizing all log(n) values int val = 1 ptr = 0 ; for ( int i = 1 ; i < sz ; i ++ ) { logn [ i ] = ptr -1 ; if ( val == i ) { val *= 2 ; logn [ i ] = ptr ; ptr ++ ; } } } /** * Euler Walk ( preorder traversal) * converting tree to linear depthArray * Time Complexity : O(n) * */ void dfs ( int cur int prev int dep ) { // marking FAI for cur node if ( FAI [ cur ] == -1 ) FAI [ cur ] = ptr ; level [ cur ] = dep ; // pushing root to euler walk euler . push_back ( cur ); // incrementing euler walk pointer ptr ++ ; for ( auto x : adj [ cur ]) { if ( x != prev ) { dfs ( x cur dep + 1 ); // pushing cur again in backtrack // of euler walk euler . push_back ( cur ); // increment euler walk pointer ptr ++ ; } } } // Create Level depthArray corresponding // to the Euler walk Array void makeArr () { for ( auto x : euler ) depthArr . push_back ( level [ x ]); } int LCA ( int u int v ) { // trivial case if ( u == v ) return u ; if ( FAI [ u ] > FAI [ v ]) swap ( u v ); // doing RMQ in the required range return euler [ query ( FAI [ u ] FAI [ v ])]; } void addEdge ( int u int v ) { adj [ u ]. push_back ( v ); adj [ v ]. push_back ( u ); } int main ( int argc char const * argv []) { // constructing the described tree int numberOfNodes = 8 ; addEdge ( 1 2 ); addEdge ( 1 3 ); addEdge ( 2 4 ); addEdge ( 2 5 ); addEdge ( 2 6 ); addEdge ( 3 7 ); addEdge ( 3 8 ); // performing required precalculations preprocess (); // doing the Euler walk ptr = 0 ; memset ( FAI -1 sizeof ( FAI )); dfs ( 1 0 0 ); // creating depthArray corresponding to euler[] makeArr (); // building sparse table buildSparseTable ( depthArr . size ()); cout < < 'LCA(67) : ' < < LCA ( 6 7 ) < < ' n ' ; cout < < 'LCA(64) : ' < < LCA ( 6 4 ) < < ' n ' ; return 0 ; }
Java // Java program to demonstrate LCA of n-ary // tree in constant time. import java.util.ArrayList ; import java.util.Arrays ; class GFG { static int sz = 101 ; @SuppressWarnings ( 'unchecked' ) // Stores the tree static ArrayList < Integer >[] adj = new ArrayList [ sz ] ; // Tracks the eulerwalk static ArrayList < Integer > euler = new ArrayList <> (); // Depth for each node corresponding static ArrayList < Integer > depthArr = new ArrayList <> (); // to eulerwalk // Stores first appearance index of every node static int [] FAI = new int [ sz ] ; // Stores depth for all nodes in the tree static int [] level = new int [ sz ] ; // Pointer to euler walk static int ptr ; // Sparse table static int [][] dp = new int [ sz ][ 18 ] ; // Stores log values static int [] logn = new int [ sz ] ; // Stores power of 2 static int [] p2 = new int [ 20 ] ; static void buildSparseTable ( int n ) { // Initializing sparse table for ( int i = 0 ; i < sz ; i ++ ) { for ( int j = 0 ; j < 18 ; j ++ ) { dp [ i ][ j ] = - 1 ; } } // Filling base case values for ( int i = 1 ; i < n ; i ++ ) dp [ i - 1 ][ 0 ] = ( depthArr . get ( i ) > depthArr . get ( i - 1 )) ? i - 1 : i ; // dp to fill sparse table for ( int l = 1 ; l < 15 ; l ++ ) for ( int i = 0 ; i < n ; i ++ ) if ( dp [ i ][ l - 1 ] != - 1 && dp [ i + p2 [ l - 1 ]][ l - 1 ] != - 1 ) dp [ i ][ l ] = ( depthArr . get ( dp [ i ][ l - 1 ] ) > depthArr . get ( dp [ i + p2 [ l - 1 ]][ l - 1 ] )) ? dp [ i + p2 [ l - 1 ]][ l - 1 ] : dp [ i ][ l - 1 ] ; else break ; } static int query ( int l int r ) { int d = r - l ; int dx = logn [ d ] ; if ( l == r ) return l ; if ( depthArr . get ( dp [ l ][ dx ] ) > depthArr . get ( dp [ r - p2 [ dx ]][ dx ] )) return dp [ r - p2 [ dx ]][ dx ] ; else return dp [ l ][ dx ] ; } static void preprocess () { // Memorizing powers of 2 p2 [ 0 ] = 1 ; for ( int i = 1 ; i < 18 ; i ++ ) p2 [ i ] = p2 [ i - 1 ] * 2 ; // Memorizing all log(n) values int val = 1 ptr = 0 ; for ( int i = 1 ; i < sz ; i ++ ) { logn [ i ] = ptr - 1 ; if ( val == i ) { val *= 2 ; logn [ i ] = ptr ; ptr ++ ; } } } // Euler Walk ( preorder traversal) converting // tree to linear depthArray // Time Complexity : O(n) static void dfs ( int cur int prev int dep ) { // Marking FAI for cur node if ( FAI [ cur ] == - 1 ) FAI [ cur ] = ptr ; level [ cur ] = dep ; // Pushing root to euler walk euler . add ( cur ); // Incrementing euler walk pointer ptr ++ ; for ( Integer x : adj [ cur ] ) { if ( x != prev ) { dfs ( x cur dep + 1 ); // Pushing cur again in backtrack // of euler walk euler . add ( cur ); // Increment euler walk pointer ptr ++ ; } } } // Create Level depthArray corresponding // to the Euler walk Array static void makeArr () { for ( Integer x : euler ) depthArr . add ( level [ x ] ); } static int LCA ( int u int v ) { // Trivial case if ( u == v ) return u ; if ( FAI [ u ] > FAI [ v ] ) { int temp = u ; u = v ; v = temp ; } // Doing RMQ in the required range return euler . get ( query ( FAI [ u ] FAI [ v ] )); } static void addEdge ( int u int v ) { adj [ u ] . add ( v ); adj [ v ] . add ( u ); } // Driver code public static void main ( String [] args ) { for ( int i = 0 ; i < sz ; i ++ ) { adj [ i ] = new ArrayList <> (); } // Constructing the described tree int numberOfNodes = 8 ; addEdge ( 1 2 ); addEdge ( 1 3 ); addEdge ( 2 4 ); addEdge ( 2 5 ); addEdge ( 2 6 ); addEdge ( 3 7 ); addEdge ( 3 8 ); // Performing required precalculations preprocess (); // Doing the Euler walk ptr = 0 ; Arrays . fill ( FAI - 1 ); dfs ( 1 0 0 ); // Creating depthArray corresponding to euler[] makeArr (); // Building sparse table buildSparseTable ( depthArr . size ()); System . out . println ( 'LCA(67) : ' + LCA ( 6 7 )); System . out . println ( 'LCA(64) : ' + LCA ( 6 4 )); } } // This code is contributed by sanjeev2552
Python3 # Python program to demonstrate LCA of n-ary tree # in constant time. from typing import List # stores the tree adj = [[] for _ in range ( 101 )] # tracks the eulerwalk euler = [] # depth for each node corresponding to eulerwalk depthArr = [] # stores first appearance index of every node FAI = [ - 1 ] * 101 # stores depth for all nodes in the tree level = [ 0 ] * 101 # pointer to euler walk ptr = 0 # sparse table dp = [[ - 1 ] * 18 for _ in range ( 101 )] # stores log values logn = [ 0 ] * 101 # stores power of 2 p2 = [ 0 ] * 20 def buildSparseTable ( n : int ): # initializing sparse table for i in range ( n ): dp [ i ][ 0 ] = i - 1 if depthArr [ i ] > depthArr [ i - 1 ] else i # dp to fill sparse table for l in range ( 1 15 ): for i in range ( n ): if dp [ i ][ l - 1 ] != - 1 and dp [ i + p2 [ l - 1 ]][ l - 1 ] != - 1 : dp [ i ][ l ] = dp [ i + p2 [ l - 1 ]][ l - 1 ] if depthArr [ dp [ i ][ l - 1 ] ] > depthArr [ dp [ i + p2 [ l - 1 ]][ l - 1 ]] else dp [ i ][ l - 1 ] else : break def query ( l : int r : int ) -> int : d = r - l dx = logn [ d ] if l == r : return l if depthArr [ dp [ l ][ dx ]] > depthArr [ dp [ r - p2 [ dx ]][ dx ]]: return dp [ r - p2 [ dx ]][ dx ] else : return dp [ l ][ dx ] def preprocess (): global ptr # memorizing powers of 2 p2 [ 0 ] = 1 for i in range ( 1 18 ): p2 [ i ] = p2 [ i - 1 ] * 2 # memorizing all log(n) values val = 1 ptr = 0 for i in range ( 1 101 ): logn [ i ] = ptr - 1 if val == i : val *= 2 logn [ i ] = ptr ptr += 1 def dfs ( cur : int prev : int dep : int ): global ptr # marking FAI for cur node if FAI [ cur ] == - 1 : FAI [ cur ] = ptr level [ cur ] = dep # pushing root to euler walk euler . append ( cur ) # incrementing euler walk pointer ptr += 1 for x in adj [ cur ]: if x != prev : dfs ( x cur dep + 1 ) # pushing cur again in backtrack # of euler walk euler . append ( cur ) # increment euler walk pointer ptr += 1 # Create Level depthArray corresponding # to the Euler walk Array def makeArr (): global depthArr for x in euler : depthArr . append ( level [ x ]) def LCA ( u : int v : int ) -> int : # trivial case if u == v : return u if FAI [ u ] > FAI [ v ]: u v = v u # doing RMQ in the required range return euler [ query ( FAI [ u ] FAI [ v ])] def addEdge ( u v ): adj [ u ] . append ( v ) adj [ v ] . append ( u ) # constructing the described tree numberOfNodes = 8 addEdge ( 1 2 ) addEdge ( 1 3 ) addEdge ( 2 4 ) addEdge ( 2 5 ) addEdge ( 2 6 ) addEdge ( 3 7 ) addEdge ( 3 8 ) # performing required precalculations preprocess () # doing the Euler walk ptr = 0 FAI = [ - 1 ] * ( numberOfNodes + 1 ) dfs ( 1 0 0 ) # creating depthArray corresponding to euler[] makeArr () # building sparse table buildSparseTable ( len ( depthArr )) print ( 'LCA(67) : ' LCA ( 6 7 )) print ( 'LCA(64) : ' LCA ( 6 4 ))
C# // C# program to demonstrate LCA of n-ary // tree in constant time. using System ; using System.Collections.Generic ; public class GFG { static int sz = 101 ; // Stores the tree static List < int > [] adj = new List < int > [ sz ]; // Tracks the eulerwalk static List < int > euler = new List < int > (); // Depth for each node corresponding static List < int > depthArr = new List < int > (); // to eulerwalk // Stores first appearance index of every node static int [] FAI = new int [ sz ]; // Stores depth for all nodes in the tree static int [] level = new int [ sz ]; // Pointer to euler walk static int ptr ; // Sparse table static int [] dp = new int [ sz 18 ]; // Stores log values static int [] logn = new int [ sz ]; // Stores power of 2 static int [] p2 = new int [ 20 ]; static void buildSparseTable ( int n ) { // Initializing sparse table for ( int i = 0 ; i < sz ; i ++ ) { for ( int j = 0 ; j < 18 ; j ++ ) { dp [ i j ] = - 1 ; } } // Filling base case values for ( int i = 1 ; i < n ; i ++ ) dp [ i - 1 0 ] = ( depthArr [ i ] > depthArr [ i - 1 ]) ? i - 1 : i ; // dp to fill sparse table for ( int l = 1 ; l < 15 ; l ++ ) for ( int i = 0 ; i < n ; i ++ ) if ( dp [ i l - 1 ] != - 1 && dp [ i + p2 [ l - 1 ] l - 1 ] != - 1 ) dp [ i l ] = ( depthArr [ dp [ i l - 1 ]] > depthArr [ dp [ i + p2 [ l - 1 ] l - 1 ]]) ? dp [ i + p2 [ l - 1 ] l - 1 ] : dp [ i l - 1 ]; else break ; } static int query ( int l int r ) { int d = r - l ; int dx = logn [ d ]; if ( l == r ) return l ; if ( depthArr [ dp [ l dx ]] > depthArr [ dp [ r - p2 [ dx ] dx ]]) return dp [ r - p2 [ dx ] dx ]; else return dp [ l dx ]; } static void preprocess () { // Memorizing powers of 2 p2 [ 0 ] = 1 ; for ( int i = 1 ; i < 18 ; i ++ ) p2 [ i ] = p2 [ i - 1 ] * 2 ; // Memorizing all log(n) values int val = 1 ptr = 0 ; for ( int i = 1 ; i < sz ; i ++ ) { logn [ i ] = ptr - 1 ; if ( val == i ) { val *= 2 ; logn [ i ] = ptr ; ptr ++ ; } } } // Euler Walk ( preorder traversal) converting // tree to linear depthArray // Time Complexity : O(n) static void dfs ( int cur int prev int dep ) { // Marking FAI for cur node if ( FAI [ cur ] == - 1 ) FAI [ cur ] = ptr ; level [ cur ] = dep ; // Pushing root to euler walk euler . Add ( cur ); // Incrementing euler walk pointer ptr ++ ; foreach ( int x in adj [ cur ]) { if ( x != prev ) { dfs ( x cur dep + 1 ); euler . Add ( cur ); ptr ++ ; } } } // Create Level depthArray corresponding // to the Euler walk Array static void makeArr () { foreach ( int x in euler ) depthArr . Add ( level [ x ]); } static int LCA ( int u int v ) { // Trivial case if ( u == v ) return u ; if ( FAI [ u ] > FAI [ v ]) { int temp = u ; u = v ; v = temp ; } // Doing RMQ in the required range return euler [ query ( FAI [ u ] FAI [ v ])]; } static void addEdge ( int u int v ) { adj [ u ]. Add ( v ); adj [ v ]. Add ( u ); } // Driver Code static void Main ( string [] args ) { int sz = 9 ; adj = new List < int > [ sz ]; for ( int i = 0 ; i < sz ; i ++ ) { adj [ i ] = new List < int > (); } // Constructing the described tree int numberOfNodes = 8 ; addEdge ( 1 2 ); addEdge ( 1 3 ); addEdge ( 2 4 ); addEdge ( 2 5 ); addEdge ( 2 6 ); addEdge ( 3 7 ); addEdge ( 3 8 ); // Performing required precalculations preprocess (); // Doing the Euler walk ptr = 0 ; Array . Fill ( FAI - 1 ); dfs ( 1 0 0 ); // Creating depthArray corresponding to euler[] makeArr (); // Building sparse table buildSparseTable ( depthArr . Count ); Console . WriteLine ( 'LCA(67) : ' + LCA ( 6 7 )); Console . WriteLine ( 'LCA(64) : ' + LCA ( 6 4 )); } } // This code is contributed by Prince Kumar
JavaScript let adj = []; for ( let _ = 0 ; _ < 101 ; _ ++ ) { adj . push ([]); } // tracks the eulerwalk let euler = []; // depth for each node corresponding to eulerwalk let depthArr = []; // stores first appearance index of every node let FAI = new Array ( 101 ). fill ( - 1 ); // stores depth for all nodes in the tree let level = new Array ( 101 ). fill ( 0 ); // pointer to euler walk let ptr = 0 ; // sparse table let dp = []; for ( let _ = 0 ; _ < 101 ; _ ++ ) { dp . push ( new Array ( 18 ). fill ( - 1 )); } // stores log values let logn = new Array ( 101 ). fill ( 0 ); // stores power of 2 let p2 = new Array ( 20 ). fill ( 0 ); function buildSparseTable ( n ) { // initializing sparse table for ( let i = 0 ; i < n ; i ++ ) { dp [ i ][ 0 ] = i - 1 >= 0 && depthArr [ i ] > depthArr [ i - 1 ] ? i - 1 : i ; } // dp to fill sparse table for ( let l = 1 ; l < 15 ; l ++ ) { for ( let i = 0 ; i < n ; i ++ ) { if ( dp [ i ][ l - 1 ] !== - 1 && dp [ i + p2 [ l - 1 ]][ l - 1 ] !== - 1 ) { dp [ i ][ l ] = depthArr [ dp [ i ][ l - 1 ]] > depthArr [ dp [ i + p2 [ l - 1 ]][ l - 1 ]] ? dp [ i + p2 [ l - 1 ]][ l - 1 ] : dp [ i ][ l - 1 ]; } else { break ; } } } } function query ( l r ) { let d = r - l ; let dx = logn [ d ]; if ( l === r ) { return l ; } if ( depthArr [ dp [ l ][ dx ]] > depthArr [ dp [ r - p2 [ dx ]][ dx ]]) { return dp [ r - p2 [ dx ]][ dx ]; } else { return dp [ l ][ dx ]; } } function preprocess () { // memorizing powers of 2 p2 [ 0 ] = 1 ; for ( let i = 1 ; i < 18 ; i ++ ) { p2 [ i ] = p2 [ i - 1 ] * 2 ; } // memorizing all log(n) values let val = 1 ; ptr = 0 ; for ( let i = 1 ; i < 101 ; i ++ ) { logn [ i ] = ptr - 1 ; if ( val === i ) { val *= 2 ; logn [ i ] = ptr ; ptr += 1 ; } } } function dfs ( cur prev dep ) { // marking FAI for cur node if ( FAI [ cur ] === - 1 ) { FAI [ cur ] = ptr ; } level [ cur ] = dep ; // pushing root to euler walk euler . push ( cur ); // incrementing euler walk pointer ptr += 1 ; for ( let x of adj [ cur ]) { if ( x !== prev ) { dfs ( x cur dep + 1 ); // pushing cur again in backtrack // of euler walk euler . push ( cur ); // increment euler walk pointer ptr += 1 ; } } } // Create Level depthArray corresponding // to the Euler walk Array function makeArr () { for ( let x of euler ) { depthArr . push ( level [ x ]); } } function LCA ( u v ) { // trivial case if ( u === v ) { return u ; } if ( FAI [ u ] > FAI [ v ]) { [ u v ] = [ v u ]; } // doing RMQ in the required range return euler [ query ( FAI [ u ] FAI [ v ])]; } function addEdge ( u v ) { adj [ u ]. push ( v ); adj [ v ]. push ( u ); } // constructing the described tree let numberOfNodes = 8 ; addEdge ( 1 2 ); addEdge ( 1 3 ); addEdge ( 2 4 ); addEdge ( 2 5 ); addEdge ( 2 6 ); addEdge ( 3 7 ); addEdge ( 3 8 ); // performing required precalculations preprocess (); // doing the Euler walk ptr = 0 ; FAI = new Array ( numberOfNodes + 1 ). fill ( - 1 ); dfs ( 1 0 0 ); // creating depthArray corresponding to euler[] makeArr (); // building sparse table buildSparseTable ( depthArr . length ); console . log ( 'LCA(67) : ' LCA ( 6 7 )); console . log ( 'LCA(64) : ' LCA ( 6 4 ));
Saída
LCA(67) : 1 LCA(64) : 2
Observação : Estamos pré-calculando toda a potência necessária de 2 e também pré-calculando todos os valores de log necessários para garantir uma complexidade de tempo constante por consulta. Caso contrário, se fizéssemos o cálculo do log para cada operação de consulta, nossa complexidade de tempo não teria sido constante.
Complexidade de tempo: O processo de conversão de LCA para RMQ é feito pelo Euler Walk que leva Sobre) tempo.
O pré-processamento da tabela esparsa em RMQ leva tempo O (nlogn) e responder a cada consulta é um processo de tempo constante. Portanto, a complexidade geral do tempo é O (nlogn) - pré-processamento e O(1) para cada consulta.
Espaço Auxiliar: O(n+s)
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