Shaking table tests of a two-storey log house

This paper presents the findings of an experimental campaign that was conducted to investigate the seismic behaviour of log houses. A two-storey log house designed by the Portuguese company Rusticasa® was subjected to a series of shaking table tests at LNEC, Lisbon, Portugal. The paper contains the description of the geometry and construction of the house and all the aspects related to the testing procedure, namely the pre-design, the setup, instrumentation and the testing process itself. The shaking table tests were carried out with a scaled spectrum of the Montenegro (1979) earthquake, at increasing levels of PGA, starting from 0.07g, moving on to 0.28g and finally 0.5g. The log house did not suffer any major damage and remained in working condition throughout the entire process. The preliminary analysis of the overall behaviour of the log house is also discussed.

Analysis of the seismic performance of a two storey log house

The dearth of knowledge on the load resistance mechanisms of log houses and the need for developing numerical models that are capable of simulating the actual behaviour of these structures has pushed efforts to research the relatively unexplored aspects of log house construction. The aim of the research that is presented in this paper is to build a working model of a log house that will contribute toward understanding the behaviour of these structures under seismic loading. The paper presents the results of a series of shaking table tests conducted on a log house and goes on to develop a numerical model of the tested house. The finite element model has been created in SAP2000 and validated against the experimental results. The modelling assumptions and the difficulties involved in the process have been described and, finally, a discussion on the effects of the variation of different physical and material parameters on the results yielded by the model has been drawn up.

Using students’ learning style to create effective learning groups in MCSCL environments

Students have different ways for learning and processing information. Some students prefer learning through seeing while others prefer learning through listening; some students prefer doing activities while other prefer reflecting.Some students reason logically, while others reason intuitively, etc. Identifying the learning style of each student, and providing learning content based on these styles represents a good method to enhance the learning quality. However, there are no efforts onhow to detect the students’ learning styles in mobile computer supported collaborative learning (MCSCL) environments. We present in this paper new ways for automatically detecting the learning styles of students in MCSCL environments based on the learning style model of Felder-Silverman. The identified learning styles of students could be then stored and used at anytime toassign each one of them to his/her appropriate learning group.

Attachment style impacts behavior and early oculomotor response to positive, but not negative, pictures

The present study investigated whether oculomotor behavior is influenced by attachment styles. The Relationship Scales Questionnaire was used to assess attachment styles of forty-eight voluntary university students and to classify them into attachment groups (secure, preoccupied, fearful, and dismissing). Eye-tracking was recorded while participants engaged in a 3-seconds free visual exploration of stimuli presenting either a positive or a negative picture together with a neutral picture, all depicting social interactions. The task consisted in identifying whether the two pictures depicted the same emotion. Results showed that the processing of negative pictures was impermeable to attachment style, while the processing of positive pictures was significantly influenced by individual differences in insecure attachment. The groups highly avoidant regarding to attachment (dismissing and fearful) showed reduced accuracy, suggesting a higher threshold for recognizing positive emotions compared to the secure group. The groups with higher attachment anxiety (preoccupied and fearful) showed differences in automatic capture of attention, in particular an increased delay preceding the first fixation to a picture of positive emotional valence. Despite lenient statistical thresholds induced by the limited sample size of some groups (p < 0.05 uncorrected for multiple comparisons), the current findings suggest that the processing of positive emotions is affected by attachment styles. These results are discussed within a broader evolutionary framework.