The impact of pre‐service field training sessions on the probability of future teachers using ICT in school

Most industrialised countries have adopted training strategies for pre‐service teachers that place experienced teacher guidance centre stage, particularly within the context of regular pre‐service field training sessions. In this article, after analysing the data taken from a longitudinal survey on the computer skills and attitudes of students toward the integration of ICT in teaching in primary and secondary school teacher education programmes at the University of Sherbrooke, the authors underline the potential contradictory effects between the classroom teaching observed during practicum and the effort to support the use of computer technology in school during university training. They conclude by underlining the importance of supporting the professional development of practising teachers regarding the use of ICT, with the aim of changing practices observed by students in training and optimising the probability of increasing the use of these technologies in their future role as teachers.     

Weighted Word Pairs for query expansion

This paper proposes a novel query expansion method to improve accuracy of text retrieval systems. Our method makes use of a minimal relevance feedback to expand the initial query with a structured representation composed of weighted pairs of words. Such a structure is obtained from the relevance feedback through a method for pairs of words selection based on the Probabilistic Topic Model. We compared our method with other baseline query expansion schemes and methods. Evaluations performed on TREC-8 demonstrated the effectiveness of the proposed method with respect to the baseline.     

Transmission Line Circuit Models for Dielectric Waveguide

A general procedure is outlined for obtaining single or coupled transmission line models to represent the propagation of surface wave modes in conductively unshielded dielectric waveguides. The procedure uses a homogeneous electrically or magnetically walled waveguide having the same dimensions as the dielectric of the surface waveguide, to produce a set of orthogonal eigenfunctions. These eigenfunctions are projected upon Maxwell's equations resulting in a system of transmission lines coupled together through a wave immittance, which represents the ratio of a longitudinal and a transverse field component at the dielectric-air interface. Examples are given for various modes of the dielectric slab and the dielectric rod, in particular the HE_1n modes for the latter. The transmission line models derived for these examples consist of a single trasmission line found directly by projection or reduced from a coupled transmission line model by port elimination, or of two transmission lines coupled together. All circuit models derived preserve the basic properties of surface waves (e.g. no solution below cut-off), and any of the single line models can be solved to give explicit approximate algebraic formulae for the propagation constant as a function of frequency. Numerical results show that the dispersion curves calculated from the models versus exact values are generally excellent over the entire frequency spectrum.     

Dynamic sitting: Measurement and associations with metabolic health

Dynamic sitting, such as fidgeting and desk work, might be associated with health, but remains difficult to identify out of accelerometry data. We examined, in a laboratory study, whether dynamic sitting can be identified out of triaxial activity counts. Among 18 participants (56% men, 27.3 ± 6.5 years), up to 236 counts per minute were recorded in the anteroposterior and mediolateral axes during dynamic sitting using a hip-worn accelerometer. Subsequently, we examined in 621 participants (38% men, 80.0 ± 4.7 years) from the AGES-Reykjavik Study whether dynamic sitting was associated with cardio-metabolic health. Compared to participants who recorded the fewest dynamic sitting minutes (Q₁), those with more dynamic sitting minutes had a lower BMI (Q₂ = ?1.39 (95%CI = ?2.33;–0.46); Q₃ = ?1.87 (?2.82;–0.92); Q₄ = ?3.38 (?4.32;–2.45)), a smaller waist circumference (Q₂ = ?2.95 (?5.44;–0.46); Q₃ = ?3.47 (?6.01;–0.93); Q₄ = ?8.21 (?10.72;–5.71)), and a lower odds for the metabolic syndrome (Q₂ = 0.74 [0.45;1.20] Q₃ = 0.58 [0.36;0.95]; Q₄ = 0.36 [0.22;0.59]). Our findings suggest that dynamic sitting might be identified using accelerometry and that this behaviour was associated with health. This might be important given the large amounts of time people spend sitting. Future studies with a focus on validation, causation and physiological pathways are needed to further examine the possible relevance of dynamic sitting.     

Sports mega-events in the perception of the local community: the case of Itaquera region in São Paulo at the 2014 FIFA World Cup Brazil

Hosting sporting mega-events involve considerable investment in and significant engagement with local communities. This paper contributes to the burgeoning literature about sporting mega event’s socio-geographical impacts on tourism, employment, urban regeneration, and socio-economic and cultural benefits. Within the context of 2014 FIFA World Cup in Brazil, we assess, utilizing interview data from local communities, the impact of the construction of the 2014 World Cup’s opening venue, ‘Arena Corinthians’ soccer stadium, in Itaquera, as well as other infrastructure developments more widely in the East Zone of São Paulo. The results point to the diversity of opinions among the resident community about the real legacies resulting from this sport mega-event.     

Ground reaction forces during steeplechase hurdling and waterjumps

Athletes in the 3,000 m steeplechase track and field event negotiate unmovable hurdles and waterjumps. Ground reaction forces (GRF) in the steeplechase were quantified to elucidate injury risks / mechanisms and to inform coaches. Five male and five female steeplechasers participated. GRF were measured during treadmill running, and using specially mounted force platforms, during hurdle and waterjump takeoffs and landings at 5.54 m/s (males) or 5.00 m/s (females). Results are presented as: male mean ± SD / female mean ± SD. Initial and active peaks of vertical GRF during treadmill running were 2.04 ± 0.72 / 2.25 ± 0.28 BW and 3.11 ± 0.27 / 2.98 ± 0.24 BW. Compared to treadmill running, peak vertical forces were greater (p < 0.001) for: hurdle takeoff (initial: 4.25 ± 0.86 / 3.78 ± 0.60 BW, active: 3.82 ± 0.20 / 3.74 ± 0.32 BW), hurdle landing (active: 4.41 ± 1.13 / 4.21 ± 0.21 BW), waterjump takeoff (initial: 4.32 ± 0.67 / 4.56 ± 0.54 BW, active: 4.00 ± 0.24 / 3.83 ± 0.31 BW), and waterjump landing (initial: 3.45 ± 0.34 / #3.78 ± 0.32 BW, active:5.40 ± 0.78 / #6.23 ± 0.74 BW); (#) indicates not statistically compared (n = 2). Based on horizontal impulse, athletes decelerated during takeoff steps and accelerated during landing steps of both hurdling and waterjumps. Vertical GRF peaks and video indicated rearfoot strikes on the treadmill but midfoot strikes during hurdle and waterjump landings. Potentially injurious GRF occur during the steeplechase, particularly during waterjump landings (up to 7.0 BW).     

The white colour in Etruscan polychromes on terracotta: Spectroscopic identification of kaolin

The present work reports on a spectroscopic study of white colour samples collected from Etruscan polychromes on terracotta from the Cerveteri area. In particular, both white-on-red potsherds of the Orientalising period and high-value polychromes of the Archaic period were considered. The white pigment, a fundamental element in this class of artworks, was not clearly identified in previous archaeological and analytical studies, although the use of kaolin was tentatively proposed. Therefore, samples from the Monte Sughereto kaolin quarry in the Cerveteri area were also studied. The results of detailed analyses carried out using micro-Raman spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy first show that the quarry material is a high-purity kaolin containing quartz. Raman results strongly suggest that the same kind of kaolin was employed in the polychromes of the Archaic period. As to white-on red potsherds, infrared results have a key role in showing that the white pigment is a kaolin closely corresponding to the quarry material since a particular kaolin polytype (dickite) is dominant in both cases. The present work thus provides the first definitive identification of the white pigment used in Etruscan polychromes on terracotta from the Cerveteri area, and suggests that the source of kaolin might be the Monte Sughereto quarry.     

Detecting ethnicity-targeted hate speech in Russian social media texts

Ethnicity-targeted hate speech has been widely shown to influence on-the-ground inter-ethnic conflict and violence, especially in such multi-ethnic societies as Russia. Therefore, ethnicity-targeted hate speech detection in user texts is becoming an important task. However, it faces a number of unresolved problems: difficulties of reliable mark-up, informal and indirect ways of expressing negativity in user texts (such as irony, false generalization and attribution of unfavored actions to targeted groups), users’ inclination to express opposite attitudes to different ethnic groups in the same text and, finally, lack of research on languages other than English. In this work we address several of these problems in the task of ethnicity-targeted hate speech detection in Russian-language social media texts. This approach allows us to differentiate between attitudes towards different ethnic groups mentioned in the same text – a task that has never been addressed before. We use a dataset of over 2,6M user messages mentioning ethnic groups to construct a representative sample of 12K instances (ethnic group, text) that are further thoroughly annotated via a special procedure. In contrast to many previous collections that usually comprise extreme cases of toxic speech, representativity of our sample secures a realistic and, therefore, much higher proportion of subtle negativity which additionally complicates its automatic detection. We then experiment with four types of machine learning models, from traditional classifiers such as SVM to deep learning approaches, notably the recently introduced BERT architecture, and interpret their predictions in terms of various linguistic phenomena. In addition to hate speech detection with a text-level two-class approach (hate, no hate), we also justify and implement a unique instance-based three-class approach (positive, neutral, negative attitude, the latter implying hate speech). Our best results are achieved by using fine-tuned and pre-trained RuBERT combined with linguistic features, with F1-hate=0.760, F1-macro=0.833 on the text-level two-class problem comparable to previous studies, and F1-hate=0.813, F1-macro=0.824 on our unique instance-based three-class hate speech detection task. Finally, we perform error analysis, and it reveals that further improvement could be achieved by accounting for complex and creative language issues more accurately, i.e., by detecting irony and unconventional forms of obscene lexicon.     

Irony detection via sentiment-based transfer learning

Irony as a literary technique is widely used in online texts such as Twitter posts. Accurate irony detection is crucial for tasks such as effective sentiment analysis. A text’s ironic intent is defined by its context incongruity. For example in the phrase “I love being ignored”, the irony is defined by the incongruity between the positive word “love” and the negative context of “being ignored”. Existing studies mostly formulate irony detection as a standard supervised learning text categorization task, relying on explicit expressions for detecting context incongruity. In this paper we formulate irony detection instead as a transfer learning task where supervised learning on irony labeled text is enriched with knowledge transferred from external sentiment analysis resources. Importantly, we focus on identifying the hidden, implicit incongruity without relying on explicit incongruity expressions, as in “I like to think of myself as a broken down Justin Bieber – my philosophy professor.” We propose three transfer learning-based approaches to using sentiment knowledge to improve the attention mechanism of recurrent neural models for capturing hidden patterns for incongruity. Our main findings are: (1) Using sentiment knowledge from external resources is a very effective approach to improving irony detection; (2) For detecting implicit incongruity, transferring deep sentiment features seems to be the most effective way. Experiments show that our proposed models outperform state-of-the-art neural models for irony detection.     

Universities’ attractiveness to students: The Darwinism effect

Due to significant government cuts to Higher Education funding in Southern European systems, their already underfunded universities were forced to increasingly compete for students as sources of additional revenue. Concurrently, families and students that continued to afford participation in Higher Education became more selective when choosing a university, realising the riskier investment that Higher Education participation had become. Through a competing destinations model and relying on all Italian private and public universities, this study finds that the competition forces characterising universities’ attractiveness over the last decade have changed since the financial crisis of 2008. In a context of lower demand for Higher Education, the competition for students grew and universities in close proximity were better prepared to face the new challenges, leading to the growth of Higher Education clusters.