Princess in Danger

Princess crisis

English text is not available in this practice contest.

A brave princess in a poor country's tomboy is married to another country for a political marriage. However, a villain who was trying to kill the princess attacked him on the way to his wife, and the princess was seriously injured and was taken to a nearby hospital. However, the villain used a special poison to make sure the princess was dead. Therefore, in order to help the princess, she had to hurry to bring special medicine and frozen relatives' blood from her home country.

This blood is transported frozen, but must be re-frozen in a blood freezing facility within up to M minutes of the previous freezing to keep it fresh. However, there are only a few places where refrigeration facilities are installed.

Blood is safe for M minutes from a fully frozen state without refreezing. If the remaining time without refrigeration is S minutes and the product is transported without freezing for T minutes, the remaining time without refrigeration is S-T minutes. The remaining time that does not require refreezing can be restored up to M minutes by refreezing. The time it takes to refreeze blood depends on how much it is frozen. Every minute the blood is frozen in a freezing facility, the remaining time that does not need to be re-frozen recovers by 1 minute.

At the time of departure from the capital of the home country, the remaining time without refrigerating the blood is M minutes.

As a princess's servant, you must calculate the route to keep the blood fresh from the capital of your home country to the hospital where the princess was transported, in order to save the life of your precious lord. Yes, your mission is to figure out the shortest route from your home capital to the hospital and find the shortest time.

Input

The input consists of multiple datasets. The first row of each dataset contains six non-negative integers N (2 ≤ N ≤ 100), M (1 ≤ M ≤ 100), L (0 ≤ L ≤ N-2), K, A (0 ≤). A <N) and H (0 ≤ H <N) are given. These are the number of towns, the time limit for refrigeration, the number of towns with freezing facilities, the number of roads connecting towns directly, the number representing the capital of the home country, and the hospital where the princess was transported. Represents the town number. The capital of the home country and the hospital where the princess was transported are different towns. It is assumed that the towns are assigned numbers from 0 to N-1. The following lines are given L non-negative integers separated by a single space. These represent the numbers of the towns where the freezing facilities are located. The capital of the home country and the hospital where the princess was transported are not included in this list, but it can be considered that there is a freezing facility. The following line K gives information on the roads connecting the towns. In the i-th line, three non-negative integers X, Y, and T are given separated by one space, which means that there is a direct connection between town X and town Y, and it takes time T to move. Represents that. This road is bidirectional. Also, there is at most one road that directly connects town X and town Y.

The input ends when N = M = L = K = A = H = 0, which is not included in the dataset.

Output

For each dataset, output the shortest time that blood can be delivered while maintaining its freshness. If it cannot be delivered, output "Help!".

Sample Input


2 1 0 1 0 1
0 1 2
3 1 1 2 0 1
2
0 2 1
1 2 1
3 2 1 2 0 1
2
0 2 1
1 2 1
4 4 1 4 1 3
2
0 1 2
1 2 4
0 2 1
3 0 3
5 3 2 6 0 3
1 2
2 1 2
1 0 1
3 4 1
2 4 1
4 1 2
2 0 2
5 4 2 6 0 3
1 2
4 2 4
2 1 2
4 3 1
0 1 5
1 4 2
2 0 3
0 0 0 0 0 0


Output for the Sample Input


Help!
3
2
Ten
Five
12






Example

Input

2 1 0 1 0 1
0 1 2
3 1 1 2 0 1
2
0 2 1
1 2 1
3 2 1 2 0 1
2
0 2 1
1 2 1
4 4 1 4 1 3
2
0 1 2
1 2 4
0 2 1
3 0 3
5 3 2 6 0 3
1 2
2 1 2
1 0 1
3 4 1
2 4 1
4 1 2
2 0 2
5 4 2 6 0 3
1 2
4 2 4
2 1 2
4 3 1
0 1 5
1 4 2
2 0 3
0 0 0 0 0 0


Output

Help!
3
2
10
5
12
class Heap
	require 'forwardable'
	extend Forwardable

	def initialize
		@array = []
		@index = {}
	end

	def add(obj, key)
		@array << [obj, key]
		@index[obj] = @array.size - 1
		lift_up(@array.size - 1)
	end

	def swap(i, j)
		u = @array[i]
		v = @array[j]
		@index[u[0]], @index[v[0]] = j, i
		@array[i], @array[j] = v, u
	end

	def lift_up(i)
		return if i == 0
		j = (i - 1) / 2
		if @array[i][1] < @array[j][1]
			swap(i, j)
			lift_up(j)
		end
	end

	def del_min
		raise "heap is empty!" if empty?
		min = @array[0]
		if size > 1
			swap(0, @array.size-1)
			@array.pop
			lift_down(0)
		else
			@array.pop
		end
		@index.delete(min[0])
		min
	end

	def inc_key(obj, diff)
		i = @index[obj]
		@array[i][1] += diff
		lift_down(i)
	end

	def dec_key(obj, diff)
		i = @index[obj]
		@array[i][1] -= diff
		lift_up(i)
	end

	def update_key(obj, new_key)
		i = @index[obj]
		return unless i
		return if new_key >= @array[i][1]
		@array[i][1] = new_key
		lift_up(i)
	end

	def min_obj
		@array[0][0]
	end

	def min_key
		@array[0][1]
	end

	def lift_down(i)
		j = 2 * i + 1
		k = j + 1
		if k >= size
			return if j >= size
			if @array[i][1] > @array[j][1]
				swap(i, j)
				lift_down(j)
			end
		else
			l = (@array[j][1] < @array[k][1] ? j : k)
			if @array[i][1] > @array[l][1]
				swap(i, l)
				lift_down(l)
			end
		end
	end

	def_delegators :@array, :empty?, :size
end

module Graphical
	require 'set'

	def reachable_from(s, max_depth = nil)
		reached = Set[s]
		queue = [s]
		depth = 0
		loop {
			break if max_depth && depth >= max_depth
			next_queue = []
			until queue.empty?
				u = queue.shift
				each_to_node_of(u){|v|
					next if reached.include?(v)
					reached << v
					next_queue << v
				}
			end
			break if next_queue.empty?
			queue = next_queue
			depth += 1
		}
		return reached
	end

	def dijkstra(start, setting = {})
		raise "invalid setting" if setting.class != Hash
		raise "invalid setting" if setting.keys - [:goal, :multi_source, :multi_sink, :max_dist] != []
		
		start = Set[start] if !setting[:multi_source]
		goal = setting[:goal]
		goal = Set[goal] if goal && !setting[:multi_sink]
		max_dist = setting[:max_dist]

		h = Heap.new
		reached = Set.new
		start.each{|v|
			h.add(v, 0)
			reached << v
		}

		dist = {}
		until h.empty?
			u, key = h.del_min
			return key if setting[:goal] && goal.include?(u)
			break if max_dist && key > max_dist
			dist[u] = key
			each_to_node_of(u){|v|
				d = dist[u] + edge_length(u, v)
				if reached.include?(v)
					h.update_key(v, d)
				else
					h.add(v, d)
					reached << v
				end
			}
		end
		goal ? nil : dist
	end

	def bidir_dijkstra(s, t)
		f_dist = {}
		b_dist = {}

		f_heap = Heap.new
		b_heap = Heap.new

		f_heap.add(s, 0)
		b_heap.add(t, 0)

		f_reached = Set[s]
		b_reached = Set[t]

		f_current_dist = b_current_dist = 0
		best = Float::INFINITY

		loop {
			if !f_heap.empty?
				u, key = f_heap.del_min
				f_dist[u] = key
				f_current_dist = key
				each_to_node_of(u){|v|
					d = f_dist[u] + edge_length(u, v)
					if b_dist[v]
						path_len = d + b_dist[v]
						best = path_len if path_len < best
					end
					if f_reached.include?(v)
						f_heap.update_key(v, d)
					else
						f_heap.add(v, d)
						f_reached << v
					end
				}
			end

			if !b_heap.empty?
				u, key = b_heap.del_min
				b_dist[u] = key
				b_current_dist = key
				each_from_node_of(u){|v|
					d = b_dist[u] + edge_length(v, u)
					if f_dist[v]
						path_len = d + f_dist[v]
						best = path_len if path_len < best
					end
					if b_reached.include?(v)
						b_heap.update_key(v, d)
					else
						b_heap.add(v, d)
						b_reached << v
					end
				}
			end

			return best if f_current_dist + b_current_dist >= best
			return nil if f_heap.empty? && b_heap.empty?
		}
	end
end

class Graph
	include Graphical
	require 'set'

	def add_node(label = nil)
		Node.new(label)
	end

	def add_edge(u, v, label = nil)
		e = Edge.new(u, v, label)
		u.neighbour[v] = e
		v.neighbour[u] = e
		e
	end
	
	def del_edge(e)
		u, v = e.from, e.to
		u.neighbour.delete(v)
		v.neighbour.delete(u)
		e
	end

	class Node
		def initialize(label)
			@label = label
			@neighbour = {}
		end

		def to_s
			@label
		end
		
		attr_accessor :neighbour
		attr_reader :label
	end

	class Edge
		def initialize(u, v, label = nil)
			@from = u	
			@to = v
			@label = label
		end
		attr_reader :from, :to, :label
	end


	def each_to_node_of(u)
		u.neighbour.each_key{|v|
			yield v
		}
	end
	alias :each_from_node_of :each_to_node_of

	def edge_length(u, v)
		u.neighbour[v] ? 1 : nil
	end

end

class WeightedGraph < Graph
	def add_edge(u, v, length, label = nil)
		e = Edge.new(u, v, length, label)
		u.neighbour[v] = e
		v.neighbour[u] = e
		e
	end

	class Edge
		def initialize(u, v, length, label = nil)
			@from = u	
			@to = v
			@length = length
			@label = label
		end
		attr_reader :from, :to, :length, :label
	end

	def edge_length(u, v)
		u.neighbour[v].length
	end
end


start = Time.new

def warshall_floyd(dist_matrix)
	dist = dist_matrix
	n = dist.size
	raise "dist_matrix is not square" if dist.any?{|row| row.size != n}

	(0..n-1).each{|k|
		next_dist = (1..n).map{ Array.new(n) }	
		(0..n-1).each{|i|
			(0..n-1).each{|j|
				x = dist[i][j]
				y = dist[i][k] + dist[k][j]
				next_dist[i][j] = (x < y ? x : y)
			}
		}
		dist = next_dist
	}
	dist
end

loop {
	n, m, l, k, a, h = gets.split.map &:to_i
	break if n == 0

	freezer = (gets.split.map(&:to_i) + [a, h]).sort

	g = WeightedGraph.new
	nodes = (1..n).map{ g.add_node }

	k.times {
		x, y, t = gets.split.map &:to_i
		g.add_edge(nodes[x], nodes[y], t)
	}
	
	g2 = WeightedGraph.new
	f_nodes = {}
	freezer.each{|i|
		f_nodes[i] = g2.add_node
	}

	d2 = freezer.map{|x|
		d = g.dijkstra(nodes[x])
		freezer.map{|y|
			g2.add_edge(f_nodes[x], f_nodes[y], d[nodes[y]]) if d[nodes[y]]
		}
	}
	
	d = g2.dijkstra(f_nodes[a], {:goal => f_nodes[h]})
	if d
		puts d + (d < m ? 0 : d - m)
	else
		puts 'Help!'
	end
}