# Original solution




# 点更新，区間クエリ
class SegTree:
    # n : 元の配列の長さ
    # init_list: 元の配列
    # segfunc : 載せる関数（演算）
    # ide_ele : segfuncの単位元
        
    def __init__(self, n, init_list ,segfunc, ide_ele):
        #　num : 2**num >= n となる最小の整数 （葉の数）
        # seg : segtreeのリスト
        self.num = 2**((n-1).bit_length())
        self.seg = [ide_ele]*(2*self.num)
        self.segfunc = segfunc
        self.ide_ele = ide_ele
        # 葉の要素をセット
        for i in range(n):
            self.seg[i+self.num-1] = init_list[i]        
        # segtreeの構築
        for i in range(self.num-2, -1, -1):
            self.seg[i] = segfunc(self.seg[2*i+1],self.seg[2*i+2])
        
        #memo: 要素iの子ノードは要素2*i+1, 2*i+2
        #    : 要素iの親ノードは要素(i-1)//2
        
    # 要素の更新 (init_list[k]=x)
    def update(self,k,x):
        k += self.num-1 #葉のノードのインデックス
        self.seg[k] = x
        #末端から頂点まで更新
        while k:
            k = (k-1)//2
            self.seg[k] = self.segfunc(self.seg[2*k+1], self.seg[2*k+2])
     
    # 区間クエリ （区間[l,r)に対する演算結果）
    def query(self, l,r):
        if r<=l:
            return self.ide_ele
        
        l += self.num-1 #葉のノードのインデックス
        r += self.num-2 #半開区間から閉区間へ
        ret = self.ide_ele
        
        while r-l>1:
            if l&1 == 0:
                ret = self.segfunc(ret,self.seg[l])
            
            if r&1 == 1:
                ret = self.segfunc(ret,self.seg[r])
                r -= 1
            # 親ノードへ遷移
            l = l//2
            r = (r-1)//2
        if r==l:
            ret = self.segfunc(ret, self.seg[r])
        else:
            ret = self.segfunc(ret, self.seg[l])
            ret = self.segfunc(ret, self.seg[r])
        
        return ret
            
def segfunc(x,y):
    return x + y

# import sys
# input = sys.stdin.readline

N = int(eval(input()))
A = list(map(int,input().split()))
#%%
idxlist = [0]*N
for i,a in enumerate(A):
    idxlist[a-1] = i+2

A = [N+1]*2 + A + [N+1]*2
#%%
ans = 0
seg = SegTree(N+4,[1]*2+[0]*N+[1]*2,segfunc,0)

def judge(l,r,key):
    if l>r:
        l,r = r,l
    res = seg.query(l,r+1)
    if res>key:
        return False
    else:
        return True

def bsearch(idx,ng,key):
    ok = idx
    while abs(ok-ng)>1:
        mid = (ok+ng)//2
        if judge(idx,mid,key):
            ok = mid
        else:
            ng = mid
    return ng


for idx in reversed(idxlist):
    if A[idx]==N:
        seg.update(idx,1)
        continue
    ng_l = 0
    ng_r = N+3
    
    L1 = bsearch(idx,ng_l,0)
    L2 = bsearch(idx,ng_l,1)
    R1 = bsearch(idx,ng_r,0)
    R2 = bsearch(idx,ng_r,1)
    
    coef = 0
    if A[L1]!=N+1:
        coef += (L1-L2)*(R1-idx)
    if A[R1]!=N+1:
        coef += (R2-R1)*(idx-L1)
    ans += A[idx]*coef
    seg.update(idx,1)
    
print(ans)






# Optimized solution

# 1-indexed　Binary Indexed Tree
class BIT:
    def __init__(self, n, init_list):
        self.num = n+1
        self.tree = [0]*self.num
        for i,e in enumerate(init_list):
            self.update(i,e)

    def update(self,k,x):
        k = k+1
        while k < self.num:
            self.tree[k] += x
            k += (k&(-k))
        return 
    
    # sum([l,r))
    def query(self, l,r):
        ret = 0
        while r>0:
            ret += self.tree[r]
            r -= r&(-r)
        while l>0:
            ret -= self.tree[l]
            l -= l&(-l)
        
        return ret


N = int(eval(input()))
A = list(map(int,input().split()))
#%%
idxlist = [0]*N
for i,a in enumerate(A):
    idxlist[a-1] = i+2

A = [N+1]*2 + A + [N+1]*2
#%%
ans = 0
seg = BIT(N+4,[1]*2+[0]*N+[1]*2)

def judge(l,r,key):
    if l>r:
        l,r = r,l
    res = seg.query(l,r+1)
    if res>key:
        return False
    else:
        return True

def bsearch(idx,ng,key):
    ok = idx
    while abs(ok-ng)>1:
        mid = (ok+ng)//2
        if judge(idx,mid,key):
            ok = mid
        else:
            ng = mid
    return ng


for idx in reversed(idxlist):
    if A[idx]==N:
        seg.update(idx,1)
        continue
    ng_l = 0
    ng_r = N+3
    
    L1 = bsearch(idx,ng_l,0)
    L2 = bsearch(idx,ng_l,1)
    R1 = bsearch(idx,ng_r,0)
    R2 = bsearch(idx,ng_r,1)
    
    coef = 0
    if A[L1]!=N+1:
        coef += (L1-L2)*(R1-idx)
    if A[R1]!=N+1:
        coef += (R2-R1)*(idx-L1)
    ans += A[idx]*coef
    seg.update(idx,1)
    
print(ans)