- Europe should make a strong appeal to Japan to get out of the bunker and ensure that something is done about these technical barriers.
- Europa borde bestämt vädja till Japan att ta sig ur bunkern och se till att något görs i fråga om dessa tekniska hinder.
- There is no doubt that one of the barriers for the Japanese is the extremely high technical barriers that exist and have always existed in Japanese society.
- Det råder inga tvivel om att vad som hindrar Japan är de oerhört höga tekniska hinder som finns och alltid har funnits i det japanska samhället.
- That might cause Japan to look forward, to see the situation with fresh eyes, and to remove these numerous technical barriers.
- Det finns ett avsevärt behov av att företag från andra regioner träder in och hjälper till. Det skulle kunna få Japan att blicka framåt och se situationen med nya ögon, och avskaffa de många tekniska hindren.
- The availability of fuels with a maximum sulphur content of 10 parts per million will remove any remaining technical barriers to the introduction of the most fuel efficient vehicles, which will in turn provide a basis for further reductions in emissions of carbon dioxide.
- Tillgången på bränslen med ett maximalt svavelinnehåll på 10 ppm kommer att avlägsna alla återstående tekniska hinder för införandet av de mest bränslesnåla fordonen, som i sin tur kommer att utgöra grund för ytterligare minskningar av koldioxidutsläppen.
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 = 7859 AND
t12.lemma_id = 41593 AND
t21.lemma_id = 31204 AND
t22.lemma_id = 33566),
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;
;