- Madam President, road transport, along with the other sectors of the economy, must contribute to efforts to reduce CO2 emissions in a bid to achieve the Kyoto Protocol targets and our future commitments for 2020 and beyond.
- Vägtransport, tillsammans med de andra sektorerna inom ekonomin, måste bidra till att minska koldioxidutsläppen för att vi ska kunna uppnå målen i Kyotoprotokollet och våra framtida åtaganden inför 2020 och längre fram.
- the demand for ever-increasing qualifications by the labour market, which puts low-skilled jobs at risk, the spiralling increase in youth unemployment, which is over 30% in certain EU Member States, including Greece, and the failure on the part of the Member States to take adequate measures to achieve the targets set in the EU 2020 strategy (for example, to reduce the percentage of early school leavers to 10% and to increase the percentage of young people with a university education to 40%).
- Specifika utmaningar beaktas, exempelvis arbetsmarknadens krav på ökade kvalifikationer, som innebär att lågkvalificerade arbeten riskeras, den kraftigt stigande ungdomsarbetslösheten, som uppgår till över 30 procent i vissa EU-medlemsstater, däribland Grekland, och medlemsstaternas misslyckande när det gäller att vidta lämpliga åtgärder för att uppnå målen i Europa 2020-strategin (exempelvis att minska andelen ungdomar som slutar skolan i förtid till mindre än 10 procent och öka antalet ungdomar med universitetsutbildning till 40 procent).
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 = 'dobj' AND
s2.val = 'OO' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'NOUN' AND
t22.ctag = 'NOUN' AND
t11.lemma_id = 5196 AND
t12.lemma_id = 47782 AND
t21.lemma_id = 35250 AND
t22.lemma_id = 31275),
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;
;