Consider a Multi$-$Layer Perceptron $($MLP$)$ model with one hidden layer and one output layer. The hidden layer has $10$ neurons, and the output layer has $3$ neurons. The input to the MLP is a $5-$dimensional vector. Each neuron is connected to every neuron in the previous layer, and a bias term is included for each neuron. The activation function used is the sigmoid function.

Calculate the total number of trainable parameters in this MLP model.