- For ages, governments all over Europe have been closing rail services to the benefit of private companies throughout the road transport sector, leading to the tragic accidents in the Mont Blanc and Saint-Gothard tunnels and the tremendous human and social cost of all, more ’normal’, accidents.
- Denna sektor ligger bakom de tragiska olyckorna i Mont Blanc-tunneln och Saint-Gotthard-tunneln och den enorma mänskliga och sociala kostnaden för alla ”vanliga” bilolyckor.
- In full agreement with the principles of ensuring sustainable development and environmental disaster recovery as stated in the report and in the context of the two recent tragic accidents in the area of Kerch last November and in the first week of the current year, it is necessary to set up a mechanism to take into consideration the interest of local communities in coastal municipalities where there is a threat to the clean waters of the Black Sea, to the livelihoods and quality of life of citizens in these towns and villages.
- Jag instämmer helt och hållet i principerna om att skapa hållbar utveckling och återhämtning för miljön i enlighet med betänkandet, och mot bakgrund av de två tragiska olyckorna nyligen i Kerchområdet i november förra året och i början av januari i år är det nödvändigt att inrätta en mekanism för att beakta kustsamhällenas intressen i de fall det finns risker för vattenkvaliteten i Svarta havet och för försörjningen och livskvaliteten för invånarna i dessa samhällen.
show query
SET search_path TO f9miniensv;
WITH
list AS (SELECT
t11.token_id AS t11,
t12.token_id AS t12,
t21.token_id AS t21,
t22.token_id AS t22,
r1.dep_id AS dep1,
r2.dep_id AS dep2
FROM
deprel r1
JOIN depstr s1 ON s1.dep_id = r1.dep_id
JOIN word_align a1 ON a1.wsource = r1.head AND a1.wsource < a1.wtarget
JOIN word_align a2 ON a2.wsource = r1.dependent
JOIN deprel r2 ON r2.head = a1.wtarget AND r2.dependent = a2.wtarget
JOIN depstr s2 ON s2.dep_id = r2.dep_id
JOIN token t11 ON t11.token_id = r1.head
JOIN token t21 ON t21.token_id = r2.head
JOIN token t12 ON t12.token_id = r1.dependent
JOIN token t22 ON t22.token_id = r2.dependent
WHERE
s1.val = 'amod' AND
s2.val = 'AT' AND
t11.ctag = 'NOUN' AND
t21.ctag = 'NOUN' AND
t12.ctag = 'ADJ' AND
t22.ctag = 'ADJ' AND
t11.lemma_id = 35188 AND
t12.lemma_id = 29 AND
t21.lemma_id = 35068 AND
t22.lemma_id = 33668),
stats AS (SELECT
sentence_id,
count(DISTINCT token_id) AS c,
count(*) AS c_aligned,
count(DISTINCT wtarget) AS c_target
FROM
token
LEFT JOIN word_align ON wsource = token_id
WHERE
sentence_id IN (
SELECT sentence_id
FROM
list
JOIN token ON token_id IN(t11, t21)
)
GROUP BY sentence_id),
numbered AS (SELECT row_number() OVER () AS i, *
FROM
list),
sentences AS (SELECT *, .2 * (1 / (1 + exp(max(c) OVER (PARTITION BY i) - min(c) OVER (PARTITION BY i)))) +
.8 * (1 / log(avg(c) OVER (PARTITION BY i))) AS w
FROM
(
SELECT i, 1 AS n, sentence_id, ARRAY[t11,t12] AS tokens
FROM
numbered
JOIN token ON token_id = t11
UNION SELECT i, 2 AS n, sentence_id, ARRAY[t21,t22] AS tokens
FROM
numbered
JOIN token ON token_id = t21
) x
JOIN stats USING (sentence_id)
ORDER BY i, n)
SELECT
i,
n,
w,
c,
c_aligned,
c_target,
sentence_id,
string_agg(CASE WHEN lpad THEN ' ' ELSE '' END || '<span class="token' ||
CASE WHEN ARRAY[token_id] <@ tokens THEN ' hl' ELSE '' END || '">' || val || '</span>',
'' ORDER BY token_id ASC) AS s
FROM
sentences
JOIN token USING (sentence_id)
JOIN typestr USING (type_id)
GROUP BY i, n, w, c, c_aligned, c_target, sentence_id
ORDER BY w DESC, i, n;
;