Abstract
Searching for health information is one of the most popular activities on the web. In this domain, users often misspell or lack knowledge of the proper medical terms to use in queries. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the Portuguese or English language with lay or medico-scientific terminology. Here we evaluate this system's impact on the medical accuracy of the knowledge acquired during the search. Evaluation shows that simply providing these suggestions contributes to reduce the quantity of incorrect content. This indicates that even when suggestions are not clicked, they are useful either for subsequent queries' formulation or for interpreting search results. Clicking on suggestions, regardless of type, leads to answers with more correct content. An analysis by type of suggestion and user characteristics showed that the benefits of certain languages and terminologies are more perceptible in users with certain levels of English proficiency and health literacy. This suggests a personalization of this suggestion system toward these characteristics. Overall, the effect of language is more preponderant than the effect of terminology. Clicks on English suggestions are clearly preferable to clicks on Portuguese ones.

Abstract
Given the large volumes and dynamics of data that recommender systems currently have to deal with, we look at online stream based approaches that are able to cope with high throughput observations. In this paper we describe work on incremental neighborhood based and incremental matrix factorization approaches for binary ratings, starting with a general introduction, looking at various approaches and describing existing enhancements. We refer to recent work on forgetting techniques and multidimensional recommendation. We will also focus on adequate procedures for the evaluation of online recommender algorithms.

Abstract
Aggregation protocols allow for distributed lightweight computations deployed on ad-hoc networks in a peer-to-peer fashion. Due to reliance on wireless technology, the communication medium is often hostile which makes such protocols susceptible to correctness and performance issues. In this paper, we study the behavior of aggregation protocols when subject to communication failures: message loss, duplication, and network partitions. We show that resolving communication failures at the communication layer, through a simple reliable communication layer, reduces the overhead of using alternative fault tolerance techniques at upper layers, and also preserves the original accuracy and simplicity of protocols. The empirical study we drive shows that tradeoffs exist across various aggregation protocols, and there is no one-size-fits-all protocol.

Abstract
Power system reliability faces serious challenges when supply shortage occurs because of unexpected generation or transmission line outages especially during extreme weather conditions. Alternative to conventional approaches that solicit aids from the generation side, operators can now leverage the demand-side resources through a variety of electricity market mechanisms to balance the active power and enhance system reliability. The benefits of the demand response (DR) have long been recognized in many works and empirical cases. Systematic analyses, however, have never been addressed to assess the values of the market-based DR for supporting system reliability. In this paper, a case study on the performance of DR in PJM Interconnections during the 2014 North American Polar Vortex is provided to highlight the significant contributions to improving system reliability and maintaining grid stability from DR programs. The unique merits in technical, economic and environmental aspects exhibited by DR during this extreme event verse conventional system-reliability-improving approaches are also demonstrated accordingly. Furthermore, we reveal the difference of DR programs driven by various existing market mechanisms after describing the fundamental DR functions. Values of various DR programs are also highlighted. At last, challenges and opportunities facing China on the design and implementation of DR programs during the transform from the monopoly scheme to an open electricity market during the power industry restructuring in recent years are also discussed.

Abstract

Abstract
The analysis of sentiments, emotions and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative or neutral. To identify the emotional load intended by the author it is necessary also to categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three di erent levels of emotions – global, specific and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources, the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Also, this paper details the web application and web service that exploit this dictionary. It presents also a validation of the proposed approach using a corpus of student texts with di erent emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. © Maria Inês Maia and José Paulo Leal