This chapter describes and evaluates the use of Information Extraction and Natural Language Processing methods for extraction and analysis of financial annual reports in three languages: English, Spanish and Portuguese. The work described retains information on document structure which is needed to enable a clear distinction between narrative and financial statement components of annual reports and between individual sections within the narratives component. Extraction accuracy varies between languages with English exceeding 95 %. We apply the extraction methods on a comprehensive sample of annual reports published by UK, Spanish and Portuguese non-financial firms between 2003 and 2014.

Antinociception induced by the adenosine A1 receptor agonist N6-cyclopentyladenosine (CPA) is linked to opioid receptors. We studied the subtype of receptors to which CPA action is related, as well as a possible enhancement of antinociception when CPA is coadministered with opioid receptor agonists. Spinal cord neuronal nociceptive responses of male Wistar rats with inflammation were recorded using the single motor unit technique. CPA antinociception was challenged with naloxone or norbinaltorphimine. The antinociceptive activity of fentanyl and U-50488H was studied alone and combined with CPA. Reversal of CPA antinociception was observed with norbinaltorphimine (82.9±13% of control) but not with low doses of naloxone (27±8% of control), indicating an involvement of κ-opioid but not µ-opioid receptors. Low doses of CPA did not modify fentanyl antinociception. However, a significant enhancement of the duration of antinociception was seen when U-50488H was coadministered with CPA. We conclude that antinociception mediated by CPA in the spinal cord is associated with activation of κ-opioid but not µ-opioid receptors in inflammation. In addition, coadministration of CPA and κ-opioid receptor agonists is followed by significantly longer antinociception, opening new perspectives in the treatment of chronic inflammatory pain.

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This paper presents a translingual study of medical lexicology in English and Japanese that compares the meaning and usage of three suffixes often found in medical discourse: -gram, -graph and -graphy. By means of an in-depth observation of frequency counts and semantic profiling in actual usage, we present a proposal regarding which roots each of the suffixes allow, together with an analysis of the meaning subtleties of the affixes. This work, informed by both cognitive and corpus linguistics, advances the presence of a concurrent pattern in English-Japanese morphology within medical discourse. After presenting a number of parallelisms and differences within the corpora, the work concludes with an explanation of how and why the three suffixes under inspection display quite distinct meaning nuances that restrain them from being used at random, both in English and in Japanese.

The main objective of this work is to perform a comparative analysis of sentence and main noun phrases complexity in two different types of discourses, written media and academic prose, using a trained syntactic parser (Stanford PCFG Parser). For this purpose, we have selected three written sources: a general media corpus, a medical media subcorpus and a medical academic prose subcorpus. From a total of more than 160000 sentences, we have carefully selected as the study sample a total of 300, which have been morphologically and syntactically annotated. Influenced by other studies related to syntax and statistics, our hypothesis is that NPs from academic prose and written media will contain four or more words, and those belonging to academic prose will be larger than the latter. The NPs studied are those that perform the main functions of the clause: subject, object (direct and indirect), attribute and time expressions. The results show a confirmation of our hypothesis. The academic subcorpus has the longest sentences and more complex NPs than the other texts. On the other hand, written media corpora achieve smaller NPs but their results are quite similar.