The objective function and constraints are translated into a Gurobi model.  The resource constraints (power and data integrity impact) are implemented using the provided coefficients.  Note that some constraints are redundant (e.g., the total power consumption constraint and the individual component constraints).  The integer requirements for the variables are also enforced.

```python
from gurobipy import Model, GRB

# Create a new model
m = Model("resource_optimization")

# Create variables
patches_per_day = m.addVar(vtype=GRB.INTEGER, name="patches_per_day")
pen_testers = m.addVar(vtype=GRB.INTEGER, name="pen_testers")
intrusion_analysts = m.addVar(vtype=GRB.INTEGER, name="intrusion_analysts")

# Set objective function
m.setObjective(7.19 * patches_per_day * pen_testers + 1.57 * patches_per_day * intrusion_analysts + 2.02 * pen_testers**2 + 3.09 * patches_per_day + 7.49 * pen_testers, GRB.MAXIMIZE)

# Add constraints
m.addConstr(11.44 * patches_per_day + 11.11 * pen_testers + 14.9 * intrusion_analysts <= 84, "Power Consumption") #r0
m.addConstr(12.65 * patches_per_day + 0.78 * pen_testers + 14.19 * intrusion_analysts <= 155, "Data Integrity Impact") #r1

m.addConstr(11.44 * patches_per_day + 14.9 * intrusion_analysts <= 65, "Patches and Analysts Power")
m.addConstr(12.65 * patches_per_day + 14.19 * intrusion_analysts <= 69, "Patches and Analysts Data Integrity")

m.addConstr(0.78 * pen_testers + 14.19 * intrusion_analysts <= 105, "Testers and Analysts Data Integrity")
m.addConstr(12.65 * patches_per_day + 0.78 * pen_testers <= 107, "Patches and Testers Data Integrity")
m.addConstr(12.65 * patches_per_day + 0.78 * pen_testers + 14.19 * intrusion_analysts <= 131, "Total Data Integrity Impact")


# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('patches_per_day:', patches_per_day.x)
    print('pen_testers:', pen_testers.x)
    print('intrusion_analysts:', intrusion_analysts.x)
elif m.status == GRB.INFEASIBLE:
    print('Model is infeasible')
else:
    print('Optimization ended with status %d' % m.status)

```
