Constraint not working as intended

Hello,

Thank you for reading my question. I am trying to select a series of arcs based on maximized benefit and contiguity. However, I am having trouble with constraint 5, introducing the variable aij. Aij is supposed to be 1 if xij in a neighborhood set is 1. However, my code generates a 1 for all Aijs and I cannot figure out why.  Any insights to offer? Thanks in advance.

#cost along arcs
c=[9,6,8,2,3,8,5,7,8,5,9,2,6,4,7,3,8,6,6,5,7,8,4,4,4,4,5,3,3,9,6,7]
#benefit along arcs
b=[5,2,4,6,7,4,9,3,4,9,5,6,2,8,3,7,4,2,2,9,3,4,8,8,8,8,9,7,7,5,2,3]
B = 25  #Budget
e = .1  #contiguity efficiency parameter

# Neighborhood set of arcs
Ni = [
    [1, 2, 3, 6, 5],
    [0, 2, 3, 4, 7, 8],
    [0, 1, 4, 9, 10],
    [0, 1, 4, 5, 6, 7, 8],
    [1, 2, 3, 7, 8, 9, 10],
    [0, 3, 6, 12, 16, 17],
    [0, 3, 5, 7, 11, 12, 13],
    [1, 3, 4, 6, 8, 11, 12, 13],
    [1, 3, 4, 7, 9, 11, 14, 15],
    [2, 4, 8, 10, 11, 14, 15],
    [2, 4, 9, 15, 20, 21],
    [6, 7, 8, 9, 10, 12, 13, 14, 15],
    [5, 6, 7, 11, 13, 16, 17],
    [6, 7, 11, 12, 14, 18, 19],
    [8, 9, 11, 13, 15, 18, 19],
    [8, 9, 10, 11, 14, 20, 21],
    [5, 12, 17, 23, 27, 29],
    [5, 12, 16, 18, 22, 23, 24],
    [13, 14, 17, 19, 22, 23, 24],
    [13, 14, 18, 20, 22, 25, 26],
    [10, 15, 19, 21, 22, 25, 26],
    [10, 15, 20, 26, 28, 31],
    [17, 18, 19, 20, 23, 24, 25, 26],
    [16, 17, 18, 22, 23, 24, 27, 29],
    [17, 18, 22, 23, 25, 27, 28, 30],
    [19, 20, 22, 24, 26, 27, 28, 30],
    [19, 20, 21, 22, 25, 28, 31],
    [16, 23, 24, 25, 28, 29, 30],
    [21, 24, 25, 26, 27, 30, 31],
    [16, 23, 27, 30, 31],
    [24, 25, 27, 28, 29, 31],
    [21, 26, 28, 29, 30],
]
from gurobipy import Model, GRB, quicksum

m = Model("Pedestrian")

x = {}
for ArcNum in range(0, 32):
    x[ArcNum] = m.addVar(vtype=GRB.BINARY)

a = {}
for ArcNum in range(0, 32):
    a[ArcNum] = m.addVar(vtype=GRB.BINARY)

# Budget Constraint
m.addConstr(
    quicksum(c[ArcNum] * x[ArcNum] for ArcNum in range(0, 32)),
    GRB.LESS_EQUAL,
    B,
    "BudgetConstraint",
)

# contiguity indicator aij; aij = 1 if xij has a contiguous neighbor being repaired and 0 otherwise
for ArcNum in range(0, 32):
    m.addConstr(
        a[ArcNum], GRB.LESS_EQUAL, quicksum(x[Neighbors] for Neighbors in Ni[ArcNum])
    )

m.setObjective(
    quicksum(b[ArcNum] * x[ArcNum] for ArcNum in range(0, 32))
    + (quicksum(a[ArcNum] * b[ArcNum] * e for ArcNum in range(0, 32)))
)

m.update()
m.modelSense = GRB.MAXIMIZE
m.optimize()

Gurobi Optimizer version 9.1.1 build v9.1.1rc0 (win64)
Thread count: 6 physical cores, 12 logical processors, using up to 12 threads
Optimize a model with 33 rows, 64 columns and 282 nonzeros
Model fingerprint: 0x6984ba11
Variable types: 0 continuous, 64 integer (64 binary)
Coefficient statistics:
  Matrix range     [1e+00, 9e+00]
  Objective range  [2e-01, 9e+00]
  Bounds range     [1e+00, 1e+00]
  RHS range        [3e+01, 3e+01]
Found heuristic solution: objective 22.8000000
Presolve time: 0.00s
Presolved: 33 rows, 64 columns, 282 nonzeros
Variable types: 0 continuous, 64 integer (64 binary)

Root relaxation: objective 7.530000e+01, 16 iterations, 0.00 seconds

    Nodes    |    Current Node    |     Objective Bounds      |     Work
 Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time

     0     0   75.30000    0    1   22.80000   75.30000   230%     -    0s
H    0     0                      74.3000000   75.30000  1.35%     -    0s

Cutting planes:
  Gomory: 1

Explored 1 nodes (16 simplex iterations) in 0.02 seconds
Thread count was 12 (of 12 available processors)

Solution count 2: 74.3 22.8 

Optimal solution found (tolerance 1.00e-04)
Best objective 7.430000000000e+01, best bound 7.430000000000e+01, gap 0.0000%

x
{0: <gurobi.Var C0 (value 0.0)>,
 1: <gurobi.Var C1 (value 0.0)>,
 2: <gurobi.Var C2 (value 0.0)>,
 3: <gurobi.Var C3 (value 1.0)>,
 4: <gurobi.Var C4 (value 1.0)>,
 5: <gurobi.Var C5 (value 0.0)>,
 6: <gurobi.Var C6 (value 0.0)>,
 7: <gurobi.Var C7 (value 0.0)>,
 8: <gurobi.Var C8 (value 0.0)>,
 9: <gurobi.Var C9 (value 0.0)>,
 10: <gurobi.Var C10 (value 0.0)>,
 11: <gurobi.Var C11 (value 1.0)>,
 12: <gurobi.Var C12 (value 0.0)>,
 13: <gurobi.Var C13 (value 1.0)>,
 14: <gurobi.Var C14 (value 0.0)>,
 15: <gurobi.Var C15 (value 0.0)>,
 16: <gurobi.Var C16 (value 0.0)>,
 17: <gurobi.Var C17 (value 0.0)>,
 18: <gurobi.Var C18 (value 0.0)>,
 19: <gurobi.Var C19 (value 0.0)>,
 20: <gurobi.Var C20 (value 0.0)>,
 21: <gurobi.Var C21 (value 0.0)>,
 22: <gurobi.Var C22 (value 1.0)>,
 23: <gurobi.Var C23 (value 0.0)>,
 24: <gurobi.Var C24 (value 1.0)>,
 25: <gurobi.Var C25 (value 0.0)>,
 26: <gurobi.Var C26 (value 0.0)>,
 27: <gurobi.Var C27 (value 1.0)>,
 28: <gurobi.Var C28 (value 1.0)>,
 29: <gurobi.Var C29 (value 0.0)>,
 30: <gurobi.Var C30 (value 0.0)>,
 31: <gurobi.Var C31 (value 0.0)>}

a
{0: <gurobi.Var C32 (value 1.0)>,
 1: <gurobi.Var C33 (value 1.0)>,
 2: <gurobi.Var C34 (value 1.0)>,
 3: <gurobi.Var C35 (value 1.0)>,
 4: <gurobi.Var C36 (value 1.0)>,
 5: <gurobi.Var C37 (value 1.0)>,
 6: <gurobi.Var C38 (value 1.0)>,
 7: <gurobi.Var C39 (value 1.0)>,
 8: <gurobi.Var C40 (value 1.0)>,
 9: <gurobi.Var C41 (value 1.0)>,
 10: <gurobi.Var C42 (value 1.0)>,
 11: <gurobi.Var C43 (value 1.0)>,
 12: <gurobi.Var C44 (value 1.0)>,
 13: <gurobi.Var C45 (value 1.0)>,
 14: <gurobi.Var C46 (value 1.0)>,
 15: <gurobi.Var C47 (value 1.0)>,
 16: <gurobi.Var C48 (value 1.0)>,
 17: <gurobi.Var C49 (value 1.0)>,
 18: <gurobi.Var C50 (value 1.0)>,
 19: <gurobi.Var C51 (value 1.0)>,
 20: <gurobi.Var C52 (value 1.0)>,
 21: <gurobi.Var C53 (value 1.0)>,
 22: <gurobi.Var C54 (value 1.0)>,
 23: <gurobi.Var C55 (value 1.0)>,
 24: <gurobi.Var C56 (value 1.0)>,
 25: <gurobi.Var C57 (value 1.0)>,
 26: <gurobi.Var C58 (value 1.0)>,
 27: <gurobi.Var C59 (value 1.0)>,
 28: <gurobi.Var C60 (value 1.0)>,
 29: <gurobi.Var C61 (value 1.0)>,
 30: <gurobi.Var C62 (value 1.0)>,
 31: <gurobi.Var C63 (value 1.0)>}