• The White Paper proposes to tackle this situation by gradually breaking the link between transport growth and economic growth or an increase in GDP, while recognising that economic growth will generate greater needs for mobility.
• I vitboken föreslås att man tacklar situationen genom att gradvis bryta sambandet mellan transportsektorns tillväxt och den ekonomiska tillväxten eller ökningen av BNP, samtidigt som man medger att den ekonomiska tillväxten kommer att skapa ett ökat behov av rörlighet.

• The directive tackles this problem by ensuring that the costs of treatment are reimbursed to the level guaranteed in the country of origin, or, if the treatment or procedure cost less than this sum, that the actual costs incurred are reimbursed.
• Direktivet tacklar detta problem genom att se till att vårdkostnaderna ersätts upp till garantinivån i hemlandet eller, om vården eller ingreppet kostar mindre än detta belopp, att ersättning utgår för de faktiska kostnaderna.

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 = 'prep' AND
				         t11.ctag = 'VERB' AND
				         t21.ctag = 'VERB' AND
				         t12.ctag = 'ADP' AND
				         t22.ctag = 'ADP' AND
				         t11.lemma_id = 48752 AND
				         t12.lemma_id = 6140 AND
				         t21.lemma_id = 64228 AND
				         t22.lemma_id = 27140),
	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;
;