• There is a project that involves strengthening the training of customs and police officers in the region in order to be better able to identify and work on the issue of trafficking.
• Det finns ett projekt som handlar om att förstärka utbildningen av tull och polis i regionen för att bättre kunna identifiera och arbeta med traffickingfrågan.

• I would also like to call for the Union for the Mediterranean to be strengthened both in terms of funding and in terms of commitment by the Member States, as a favoured forum for the exchange of best practice, where a clear Mediterranean policy should be established, based on partnership policy, the principle of ’ownership’ and conditionality.
• Jag efterlyser också att Medelhavsunionen förstärks, i fråga om både finansiering och åtagandet från medlemsstaterna, som ett prioriterat forum för utbyte av bästa praxis när en tydlig Medelhavspolitik ska fastställas enligt partnerskapsprincipen, principen om egenansvar och villkorlighet.

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 = 46411 AND
				         t12.lemma_id = 8748 AND
				         t21.lemma_id = 42813 AND
				         t22.lemma_id = 26495),
	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;
;