Neutrinos Confronting Large Extra Dimensions

We study neutrino physics in a model with one large extra dimension. We assume the existence of two four-dimensional branes in the five-dimensional space-time, one for the ordinary particles and the other one for mirror particles, and we investigate neutrino masses and mixings in this scheme. Comparison of experimental neutrino data with the predictions of the model leads to various restrictions on the parameters of the model. For instance, the size of the extra dimension, R, turns out to be bounded from below. Cosmological considerations seem to favor a large R. The usual mixing schemes proposed as solutions to the solar and atmospheric neutrino anomalies are compatible with our model.Comment: 19 pages, LATEX, 4 figure

A scheme with two large extra dimensions confronted with neutrino physics

We investigate a particle physics model in a six-dimensional spacetime, where two extra dimensions form a torus. Particles with Standard Model charges are confined by interactions with a scalar field to four four-dimensional branes, two vortices accommodating ordinary type fermions and two antivortices accommodating mirror fermions. We investigate the phenomenological implications of this multibrane structure by confronting the model with neutrino physics data.Comment: LATEX, 24 pages, 9 figures, minor changes in the tex

Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators

Abstract Background: Cognitive load (CL) management is essential in safety-critical fields so that professionals can monitor and control their cognitive resources efficiently to perform and solve scenarios in a timely and safe manner, even in complex and unexpected circumstances. Thus, cognitive load theory (CLT) can be used to design virtual reality (VR) training programmes for professional learning in these fields. Objectives: We studied CL management performance through behavioural indicators in authentic VR flight training and explored if and to what extent physiological data was associated with CL management performance. Methods: The expert (n = 8) and novice pilots (n = 6) performed three approach and landing scenarios with increasing element interactivity. We used video recordings of the training to assess CL management performance based on the behavioural indicators. Then, we used the heart rate (HR) and heart rate variability (HRV) data to study the associations between the physiological data and CL management performance. Results and Conclusions: The pilots performed effectively in CL management. The experience of the pilots did not remarkably explain the variation in CL management performance. The scenario with the highest element interactivity and an increase in the very low-frequency band of HRV were associated with decreased performance in CL management. Takeaways: Our study sheds light on the association between physiological indicators and CL management performance, which has traditionally been assessed with behavioural indicators in professional learning in safety-critical fields. Thus, physiological measurements can be used to supplement the assessment of CL management performance, as relying solely on behavioural indicators can be time consuming

Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming

Production function, Inefficiency, Endogeneity, Maximum likelihood, C23, D24, D83, O30, Q12,