### BUGGY CODE ###

# -*- coding: utf-8 -*-
INF = 10**15

# def dijkstra(graph, start=0, inf=INF):

#     num = len(graph)
#     remains = [node for node in range(num)]
#     dists = [inf if node != start else 0 for node in range(num)]

#     while remains:
#         min_index = min(remains, key=lambda x: dists[x])
#         remains.remove(min_index)

#         target_edges = graph[min_index]
#         for index, dist in enumerate(target_edges):
#             if dist != 0:
#                 dist_from_edge = dists[min_index] + dist
#                 if dists[index] > dist_from_edge:
#                     dists[index] = dist_from_edge

#     return dists


def dijkstra(graph, start=0, inf=INF):
    num = len(graph)
    dists = [inf if node != start else 0 for node in range(num)]
    remains = dists[:]

    for _ in range(num):
        min_index = remains.index(min(remains))
        remains[min_index] = inf

        target_edges = graph[min_index]
        for index, dist in enumerate(target_edges):
            if dist != 0:
                dist_from_edge = dists[min_index] + dist
                if dists[index] > dist_from_edge:
                    dists[index] = dist_from_edge
                    remains[index] = dist_from_edge

    return dists


n, m, s, t = map(int, input().split())
trains = [list(map(int, input().split())) for i in range(m)]

yen_graph = [[0] * n for _ in range(n)]
snuke_graph = [[0] * n for _ in range(n)]
for i, j, yen, snuke in trains:
    yen_graph[i - 1][j - 1] = yen
    yen_graph[j - 1][i - 1] = yen
    snuke_graph[i - 1][j - 1] = snuke
    snuke_graph[j - 1][i - 1] = snuke

yen_cost = dijkstra(yen_graph, start=s - 1)
snuke_cost = dijkstra(snuke_graph, start=t - 1)
costs = [yen + snuke for yen, snuke in zip(yen_cost, snuke_cost)]

for i in range(n):
    asset = 10**15
    asset -= min(costs[i:])
    print(asset)


### FIXED CODE ###

# -*- coding: utf-8 -*-
import sys
from heapq import heappop, heappush
from itertools import accumulate


def dijkstra(n, edges, start, *, adj_matrix=False, default_value=float('inf')):

    inf = float('inf')
    costs = [inf] * n
    costs[start] = 0
    pq, rem = [(0, start)], n - 1

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        if costs[tmp_node] < tmp_cost:
            continue
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value) \
                    if adj_matrix else edges[tmp_node]

        for nxt_node, nxt_cost in nxt_edges:
            new_cost = tmp_cost + nxt_cost
            if costs[nxt_node] > new_cost:
                costs[nxt_node] = new_cost
                heappush(pq, (new_cost, nxt_node))

    return costs


# n, m, s, t = map(int, input().split())
# trains = [list(map(int, l.strip().split())) for l in sys.stdin.readlines()]

# yen_edges = [[float('inf') if __ != _ else 0 for __ in range(n)]
#              for _ in range(n)]
# snuke_edges = [[float('inf') if __ != _ else 0 for __ in range(n)]
#                for _ in range(n)]
# for i, j, yen, snuke in trains:
#     yen_edges[i - 1][j - 1] = yen
#     yen_edges[j - 1][i - 1] = yen
#     snuke_edges[i - 1][j - 1] = snuke
#     snuke_edges[j - 1][i - 1] = snuke

# yen_cost = dijkstra(n, yen_edges, s - 1, adj_matrix=True)
# snuke_cost = dijkstra(n, snuke_edges, t - 1, adj_matrix=True)
# costs = [yen + snuke for yen, snuke in zip(yen_cost, snuke_cost)]

n, m, s, t = map(int, input().split())

yen_edges = [[] for _ in range(n)]
snuke_edges = [[] for _ in range(n)]
for l in sys.stdin.readlines():
    u, v, yen, snuke = map(int, l.strip().split())
# for _ in range(m):
#     u, v, yen, snuke = map(int, input().split())
    yen_edges[u - 1].append((v - 1, yen))
    yen_edges[v - 1].append((u - 1, yen))
    snuke_edges[u - 1].append((v - 1, snuke))
    snuke_edges[v - 1].append((u - 1, snuke))

yen_costs = dijkstra(n, yen_edges, s - 1)
snuke_costs = dijkstra(n, snuke_edges, t - 1)

final_costs = list(accumulate([yen + snuke for yen, snuke in zip(yen_costs, snuke_costs)][::-1], min))[::-1]
asset = 10**15
for final_cost in final_costs:
    print(asset - final_cost)