The inverted index supports efficient full-text searches on natural language text collections. It requires some extra space over the compressed text that can be traded for search speed. It is usually fast for single-word searches, yet phrase searches require more expensive intersections. In this article we introduce a different kind of index. It replaces the text using essentially the same space required by the compressed text alone (compression ratio around 35%). Within this space it supports not only decompression of arbitrary passages, but efficient word and phrase searches. Searches are orders of magnitude faster than those over inverted indexes when looking for phrases, and still faster on single-word searches when little space is available. Our new indexes are particularly fast at counting the occurrences of words or phrases. This is useful for computing relevance of words or phrases.We adapt self-indexes that succeeded in indexing arbitrary strings within compressed space to deal with large alphabets. Natural language texts are then regarded as sequences of words, not characters, to achieve word-based self-indexes. We design an architecture that separates the searchable sequence from its presentation aspects. This permits applying case folding, stemming, removing stopwords, etc. as is usual on inverted indexes. Additional Key Words and Phrases: Self-indexes, compressed data structures, inverted indexes A preliminary partial version on this work appeared in Proc. SPIRE'08 [Brisaboa et al. 2008].

INES (INtelligent Educational System) is a functionalprototype of an online learning platform, which combines three essential capabilities related to e-learning activities. These capabilities are those concerning to a LMS (Learning Management System), a LCMS (Learning Content Management System), and an ITS (Intelligent Tutoring System). To carry out all this functionalities, our system, as a whole, comprises a set of different tools and technologies, as follows: semantic managing users (administrators, teachers, students…) and contents tools, an intelligent chatterbot able to communicate with students in natural language, an intelligent agent based on BDI (Believes, Desires, Intentions) technology that acts as the brain of the system, an inference engine based on JESS (a rule engine for the Java platform) and ontologies (to modelate the user, his/her activities, and the learning contents) that contribute with the semantics of the system, etc. At the present paper we will focus on the chatterbot, CHARLIE (CHAtteR Learning Interface Entity), developed and used in the platform, which is an AIMLbased (Artificial Intelligence Markup Language) bot. We will specifically address its performance and its contribution to INES.

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This article reviews ethical issues related to genome editing using CRISPR/Cas9 system. The use of CRISPR/ cas9 revives many previous social and ethical issues with humans, other organisms and the environment, such as taking into account the non-maleficence principle in risk assessment, genome editing in germline, safety issues to avoid ecological impairment or the possible use of the technique for genetic enhancement. The new issue is the relatively simple construction and low cost of CRISPR/Cas9 for genome editing, with the possibility of multiple purposes. A public dialogue over the social, ethical and legal implications with the regulatory needs of the system is necessary.