NO

Problem:
 zeros() -> cons(0(),n__zeros())
 and(tt(),X) -> activate(X)
 length(nil()) -> 0()
 length(cons(N,L)) -> s(length(activate(L)))
 zeros() -> n__zeros()
 activate(n__zeros()) -> zeros()
 activate(X) -> X

Proof:
 Matrix Interpretation Processor: dim=3
  
  interpretation:
          [0]
   [tt] = [0]
          [0],
   
                  [1 0 0]  
   [length](x0) = [1 1 0]x0
                  [0 0 0]  ,
   
         [0]
   [0] = [0]
         [0],
   
                    [1 0 0]     [1 0 1]  
   [cons](x0, x1) = [0 0 0]x0 + [0 0 0]x1
                    [0 0 0]     [0 0 0]  ,
   
                   [1 0 0]     [1 1 1]     [1]
   [and](x0, x1) = [0 0 0]x0 + [1 1 0]x1 + [0]
                   [0 0 0]     [0 0 1]     [1],
   
             [1]
   [zeros] = [0]
             [0],
   
           [0]
   [nil] = [0]
           [0],
   
             [1 0 0]  
   [s](x0) = [0 0 0]x0
             [0 0 0]  ,
   
                    [1 0 1]     [0]
   [activate](x0) = [0 1 0]x0 + [0]
                    [0 0 1]     [1],
   
                [1]
   [n__zeros] = [0]
                [0]
  orientation:
             [1]    [1]                       
   zeros() = [0] >= [0] = cons(0(),n__zeros())
             [0]    [0]                       
   
                 [1 1 1]    [1]    [1 0 1]    [0]              
   and(tt(),X) = [1 1 0]X + [0] >= [0 1 0]X + [0] = activate(X)
                 [0 0 1]    [1]    [0 0 1]    [1]              
   
                   [0]    [0]      
   length(nil()) = [0] >= [0] = 0()
                   [0]    [0]      
   
                       [1 0 1]    [1 0 0]     [1 0 1]                          
   length(cons(N,L)) = [1 0 1]L + [1 0 0]N >= [0 0 0]L = s(length(activate(L)))
                       [0 0 0]    [0 0 0]     [0 0 0]                          
   
             [1]    [1]             
   zeros() = [0] >= [0] = n__zeros()
             [0]    [0]             
   
                          [1]    [1]          
   activate(n__zeros()) = [0] >= [0] = zeros()
                          [1]    [0]          
   
                 [1 0 1]    [0]         
   activate(X) = [0 1 0]X + [0] >= X = X
                 [0 0 1]    [1]         
  problem:
   zeros() -> cons(0(),n__zeros())
   length(nil()) -> 0()
   length(cons(N,L)) -> s(length(activate(L)))
   zeros() -> n__zeros()
   activate(n__zeros()) -> zeros()
   activate(X) -> X
  Matrix Interpretation Processor: dim=1
   
   interpretation:
    [length](x0) = 2x0,
    
    [0] = 0,
    
    [cons](x0, x1) = 2x0 + x1,
    
    [zeros] = 0,
    
    [nil] = 2,
    
    [s](x0) = x0,
    
    [activate](x0) = x0,
    
    [n__zeros] = 0
   orientation:
    zeros() = 0 >= 0 = cons(0(),n__zeros())
    
    length(nil()) = 4 >= 0 = 0()
    
    length(cons(N,L)) = 2L + 4N >= 2L = s(length(activate(L)))
    
    zeros() = 0 >= 0 = n__zeros()
    
    activate(n__zeros()) = 0 >= 0 = zeros()
    
    activate(X) = X >= X = X
   problem:
    zeros() -> cons(0(),n__zeros())
    length(cons(N,L)) -> s(length(activate(L)))
    zeros() -> n__zeros()
    activate(n__zeros()) -> zeros()
    activate(X) -> X
   Matrix Interpretation Processor: dim=3
    
    interpretation:
                      
     [length](x0) = x0
                      ,
     
           [0]
     [0] = [0]
           [0],
     
                      [1 0 0]     [1 0 1]     [1]
     [cons](x0, x1) = [1 0 0]x0 + [1 1 0]x1 + [0]
                      [0 0 0]     [1 0 0]     [0],
     
               [1]
     [zeros] = [1]
               [0],
     
               [1 0 0]  
     [s](x0) = [0 1 0]x0
               [0 0 0]  ,
     
                      [1 0 0]     [1]
     [activate](x0) = [1 1 0]x0 + [0]
                      [0 0 1]     [1],
     
                  [0]
     [n__zeros] = [1]
                  [0]
    orientation:
               [1]    [1]                       
     zeros() = [1] >= [1] = cons(0(),n__zeros())
               [0]    [0]                       
     
                         [1 0 1]    [1 0 0]    [1]    [1 0 0]    [1]                         
     length(cons(N,L)) = [1 1 0]L + [1 0 0]N + [0] >= [1 1 0]L + [0] = s(length(activate(L)))
                         [1 0 0]    [0 0 0]    [0]    [0 0 0]    [0]                         
     
               [1]    [0]             
     zeros() = [1] >= [1] = n__zeros()
               [0]    [0]             
     
                            [1]    [1]          
     activate(n__zeros()) = [1] >= [1] = zeros()
                            [1]    [0]          
     
                   [1 0 0]    [1]         
     activate(X) = [1 1 0]X + [0] >= X = X
                   [0 0 1]    [1]         
    problem:
     zeros() -> cons(0(),n__zeros())
     length(cons(N,L)) -> s(length(activate(L)))
     activate(n__zeros()) -> zeros()
    Unfolding Processor:
     loop length: 3
     terms:
      length(cons(N,n__zeros()))
      s(length(activate(n__zeros())))
      s(length(zeros()))
     context: s([])
     substitution:
      N -> 0()
     Qed