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A comprehensive study on the fluid flow and heat transfer in a nanofluid channel is carried out. The configuration of the channel is as like as quarter channel. The channel is filled with CuO–water nanofluid.

The Koo–Kleinstreuer–Li model is used to estimate the dynamic viscosity and consider the Brownian motion. On the other hand, the influence of nanoparticles’ shapes on the heat transfer rate is considered in the simulations. The channel is included with the injection pipes which are modeled as active bodies with constant temperature in the 2D simulations.

The Rayleigh number, nanoparticle concentration and the thermal arrangements of internal pipes are the governing parameters. The hydrothermal aspects of natural convection are investigation using different approaches such as average Nusselt number, total entropy generation, Bejan number, streamlines, temperature fields, local heat transfer irreversibility, local fluid friction irreversibility and heatlines.

The originality of this work is investigation of fluid flow, heat transfer, entropy generation and heatline visualization within a nanofluid-filled channel using a finite volume method.

This paper aims to investigate the individual difference on digital reading, by examining the eye-tracking records of male and female readers with different reading ability (including their pupil size, blink rate, fixation rate, fixation duration, saccade rate, saccade duration, saccade amplitude and regression rate).

A total of 74 participants were selected according to 6,520 undergraduate students’ university entrance exam scores and the follow-up reading assessments. Half of them are men and half are women, with the top 3% good readers and the bottom 3% poor readers, from different disciplines.

Results indicated that the major gender differences on reading abilities were indicated by saccade duration, regression rate and blink rate. The major effects on reading ability have a larger effect size than the major effect on gender. Among all the indicators that have been examined, blink rate and regression rates are the most sensitive to the gender attribute, while the fixation rate and saccade amplitude showed the least sensitiveness.

This finding could be helpful for user modeling with eye-tracking data in intelligent tutoring systems, where necessary adjustments might be needed according to users’ individual differences. In this way, instructors could be able to provide purposeful guidance according to what the learners had seen and personalized the experience of digital reading.