Estilos en las redes sociales en línea: un estudio basado en corpora

Das Internet wird ein immer populäreres und wichtigeres Kommunikationsmittel, besonders die sogenannten Social-Networking-Sites. In dieser Studie wird untersucht wie die Social-Networking-Sites, Facebook und Tuenti, die Kommunikation beeinflussen. In einem Korpus von Usern aus Málaga, wurde der Gebrauch von nicht-Standard Merkmalen analysiert und mit dem in der gesprochenen Sprache verglichen. Aus diesem Vergleich lässt sich schließen, dass die untersuchten sozialen und linguistischen Faktoren in der virtuellen und der reellen Sprache unterschiedlich funktionieren. Aufgrund dieses unterschiedlichen Gebrauchs kann die elektronische Kommunikation Facebook und Tuenti’s als Stil betrachtet werden, welcher den Usern dazu dient, soziale Bedeutung zu kreieren und ihre sprachliche Identität auszudrücken.

The mini-clinical evaluation exercise during medical clerkships: are learning needs and learning goals aligned?

OBJECTIVES The generation of learning goals (LGs) that are aligned with learning needs (LNs) is one of the main purposes of formative workplace-based assessment. In this study, we aimed to analyse how often trainer–student pairs identified corresponding LNs in mini-clinical evaluation exercise (mini-CEX) encounters and to what degree these LNs aligned with recorded LGs, taking into account the social environment (e.g. clinic size) in which the mini-CEX was conducted. METHODS Retrospective analyses of adapted mini-CEX forms (trainers’ and students’ assessments) completed by all Year 4 medical students during clerkships were performed. Learning needs were defined by the lowest score(s) assigned to one or more of the mini-CEX domains. Learning goals were categorised qualitatively according to their correspondence with the six mini-CEX domains (e.g. history taking, professionalism). Following descriptive analyses of LNs and LGs, multi-level logistic regression models were used to predict LGs by identified LNs and social context variables. RESULTS A total of 512 trainers and 165 students conducted 1783 mini-CEXs (98% completion rate). Concordantly, trainer–student pairs most often identified LNs in the domains of ‘clinical reasoning’ (23% of 1167 complete forms), ‘organisation/efficiency’ (20%) and ‘physical examination’ (20%). At least one ‘defined’ LG was noted on 313 student forms (18% of 1710). Of the 446 LGs noted in total, the most frequently noted were ‘physical examination’ (49%) and ‘history taking’ (21%). Corresponding LNs as well as social context factors (e.g. clinic size) were found to be predictors of these LGs. CONCLUSIONS Although trainer–student pairs often agreed in the LNs they identified, many assessments did not result in aligned LGs. The sparseness of LGs, their dependency on social context and their partial non-alignment with students’ LNs raise questions about how the full potential of the mini-CEX as not only a ‘diagnostic’ but also an ‘educational’ tool can be exploited.

Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

Annotating the meaning of discourse connectives in multilingual corpora

Discourse connectives are lexical items indicating coherence relations between discourse segments. Even though many languages possess a whole range of connectives, important divergences exist cross-linguistically in the number of connectives that are used to express a given relation. For this reason, connectives are not easily paired with a univocal translation equivalent across languages. This paper is a first attempt to design a reliable method to annotate the meaning of discourse connectives cross-linguistically using corpus data. We present the methodological choices made to reach this aim and report three annotation experiments using the framework of the Penn Discourse Tree Bank.

How comparable are parallel corpora? Measuring the distribution of general vocabulary and connectives

In this paper, we question the homogeneity of a large parallel corpus by measuring the similarity between various sub-parts. We compare results obtained using a general measure of lexical similarity based on χ2 and by counting the number of discourse connectives. We argue that discourse connectives provide a more sensitive measure, revealing differences that are not visible with the general measure. We also provide evidence for the existence of specific characteristics defining translated texts as opposed to non-translated ones, due to a universal tendency for explicitation.

Strategic Airline Alliances: Advantages for Major Airlines Being Aligned

SSome factors including the deregulation in the U.S and the liberalization in Europe of the airline industry are essential to understanding why the number of partnership agreements between airlines has increased during the last 25 years. These events, coupled with the continuous economic downturn and the 9/11 catastrophe seem to be the perfect framework for the tendency to develop airline strategic alliances. However, it has been observed that this trend was not followed during the period 2005-2008. The purpose of this paper is to analyze if a benefit was experienced by the major airlines who became a member of the current 3 big alliances compared to the major airlines that decided not to become a member or were not admitted into the alliances during 2005-2008. The methodology of this report includes an analysis of several airlines’ performance figures. These performance figures include the revenue passenger kilometers (RPKs), the passenger load factor (PLF) and also the market share (MS). The figures will be compared between the aligned airlines and others which have similar business models. The value of this paper is to reveal whether being aligned provides advantages to major airlines under a bearish airline market in a globalized environment.

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Sign.: A-P4, Q2

Silicon oxides as alignment surfaces for vertically-aligned nematics in photonic devices

A comparative study on alignment performance and microstructure of inorganic layers used for liquid crystal cell conditioning has been carried out. The study has focused on two specific materials, SiOx and SiO2, deposited under different conditions. The purpose was to establish a relationship between layer microstructure and liquid crystal alignment. The surface morphology has been studied by FESEM and AFM. An analysis on liquid crystal alignment, pretilt angle, response time, contrast ratio and the conditions to develop backflow effect (significant rise time increase due to pure homeotropic alignment) on vertically-aligned nematic cells has been carried out. A technique to overcome the presence of backflow has been identified. The full comparative study of SiOx and SiO2 layer properties and their influence over liquid crystal alignment and electrooptic response is presented.

Age regression from soft aligned face images using low computational resources

The initial step in most facial age estimation systems consists of accurately aligning a model to the output of a face detector (e.g. an Active Appearance Model). This fitting process is very expensive in terms of computational resources and prone to get stuck in local minima. This makes it impractical for analysing faces in resource limited computing devices. In this paper we build a face age regressor that is able to work directly on faces cropped using a state-of-the-art face detector. Our procedure uses K nearest neighbours (K-NN) regression with a metric based on a properly tuned Fisher Linear Discriminant Analysis (LDA) projection matrix. On FG-NET we achieve a state-of-the-art Mean Absolute Error (MAE) of 5.72 years with manually aligned faces. Using face images cropped by a face detector we get a MAE of 6.87 years in the same database. Moreover, most of the algorithms presented in the literature have been evaluated on single database experiments and therefore, they report optimistically biased results. In our cross-database experiments we get a MAE of roughly 12 years, which would be the expected performance in a real world application.