input: Write a python function to train a DecisionTreeClassifier with the given parameters and make predictions.
  assert train_and_predict(X, y, X_new) == y_pred_expected
  assert train_and_predict(X_sample1, y_sample1, X_new_sample1) == y_pred_sample1
  assert train_and_predict(X_sample2, y_sample2, X_new_sample2) == y_pred_sample2
output: def train_and_predict(X, y, X_new):
      from sklearn.tree import DecisionTreeClassifier
      
      # Initialize the classifier
      clf = DecisionTreeClassifier()
      
      # Train the classifier
      clf.fit(X, y)
      
      # Make predictions
      y_pred = clf.predict(X_new)
      
      return y_pred