Consciousness-raising tasks versus deductive approach : two form-focused instruction types in teaching grammar to Iranian high school EFL learners

Consciousness-raising (CR) task is a new way of teaching grammar developed in communicative contexts although little has been written on the effectiveness of CR tasks in EFL setting. The present study is an attempt to investigate the impact of CR tasks in Iranian EFL setting by comparing them with deductive, grammar lessons common in the Iranian schools. The subjects of this study were 80 EFL pre-university male students who were randomly assigned to an experimental group and a control one. The control group received three ordinary teacher-fronted, deductive lessons, a common way of teaching methodology in Iran, on three grammatical structures (adverb placement, indirect object placement and the use of relative clause). The experimental group, however, was treated with three &lsquo;consciousness-raising&rsquo; (CR) tasks dealing with the same target structures. The results showed that in the short-run, CR tasks were as effective as deductive approach in promoting the learners&rsquo; grammatical knowledge while in the long-run, the CR group maintained their gains more effectively than the deductive group. The conclusion is that CR tasks can function more effectively than deductive approach if the following conditions are met: (a) performing the consciousness-raising tasks in learners&rsquo; L1; (b) providing the learners with feedback whenever they encounter a problem in solving the tasks; (c) grouping the learners in such a way that at least one learner in each group would be more proficient than the other members to help the less proficient ones understand and discover the rules more effectively.<br /

Dynamic adjustment of ferrite grains during dynamic strain induced transformation

The dynamic adjustment of ferrite grains formed during \u27dynamic strain induced transformation (DSIT)\u27 is an important feature of this mechanism that has not been addressed previously. A novel experimental method was applied to follow the effect of deformation at different stages on ferrite formed initially through DSIT. It is shown that while the continuous dynamic recrystallisation (CDRX) appears to be an acceptable mechanism for re-refinement of coarser grain size (i.e. d&alpha;&gt;2dDSIT), it cannot explain the steady state grain size for finer ferrite grains (i.e. d&alpha;&lt;2dDSIT). Other potential mechanisms involved in this phenomenon are examined.<br /

A genre analysis of reprint request emails written by EFL and physics professionals

The present study aimed to analyze reprint request e-mail messages written by postgraduates (MA students) of two fields of study, namely Physics and EFL, to realize the differences and similarities between the two email types. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing<br /

(Dis)agreements in Iranians’ internet relay chats

The present study on politeness is an attempt to examine (dis)agreeing strategies utilized by EFL learners while chatting on the internet. Subjects of the study were forty male and thirty-three female Iranian natives whose internet relay chat (IRC) interactions, composed of 400 excerpts, were collected between December 2007 and September 2008. Data analysis was based on the general taxonomy of politeness strategies suggested by Brown and Levinson (1987) which is the baseline of many politeness studies today. The results indicate that IRC is a mode of communication whose characteristics are typically different from face-to-face and real-life conversational settings. Some common face threatening acts (FTAs) like &lsquo;direct disagreements&rsquo; are performed widely in chat channels. Furthermore, gender-oriented differences were found not to be statistically significant on the internet

A rare variation of the vertebral artery

Variations of the vertebrobasilar arterial complex are important with regard to their potential clinical impact. We present an unusual case of the vertebral artery, in which the left vertebral artery in its ascent in the neck through the transverse foramina passed posteriorly between the transverse processes of C3 and C4 and supplied the posterior muscles of the neck without continuing intracranially. Albeit speculatively, we hypothesise that the variation of the vertebral artery reported here was caused by degeneration of the proximal portion of the left postcostal longitudinal anastomosis (i.e. C1 and C2 intersegmental arteries) in the context of a persistent third cervical intersegmental artery. Our case is unique in that the left vertebral artery terminated extracranially. Knowledge of the variations of the vertebrobasilar arterial complex is important for surgeons operating at the skull base, craniocervical junction, and cervical region, and for clinicians interpreting the imaging of this region

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Predicting failure in solids has broad applications including earthquake prediction which remains an unattainable goal. However, recent machine learning work shows that laboratory earthquakes can be predicted using micro-failure events and temporal evolution of fault zone elastic properties. Remarkably, these results come from purely data-driven models trained with large datasets. Such data are equivalent to centuries of fault motion rendering application to tectonic faulting unclear. In addition, the underlying physics of such predictions is poorly understood. Here, we address scalability using a novel Physics-Informed Neural Network (PINN). Our model encodes fault physics in the deep learning loss function using time-lapse ultrasonic data. PINN models outperform data-driven models and significantly improve transfer learning for small training datasets and conditions outside those used in training. Our work suggests that PINN offers a promising path for machine learning-based failure prediction and, ultimately for improving our understanding of earthquake physics and prediction