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COVID-19 struck the world suddenly and unexpectedly. Since traditional education requires face-to-face communication, to avoid further spreading of the virus a majority part of that education has moved online. Our study attempts to compare the differences between online medical education with a unique course design and traditional face-to-face education. We conducted a retrospective analysis of a total of 4,098 medical students between 2019 and 2020, including two groups of students who received online education and classroom education for the same subjects, respectively. Freshmen enrolled in September 2018 received traditional classroom physiology and pharmacology education in the spring semester of 2019. Because of the impact of the COVID-19 pandemic, freshmen who were enrolled in September 2019 received online physiology and pharmacology education in the spring semester of 2020. The final marks of the two groups of students were recorded and compared. Data on students participating in online discussions, learning, homework, and watching instructional videos were also recorded. There was no significant difference in the final academic performance between the two groups [average mark: 55.93 (online education) vs. 56.27 (classroom education), P = 0.488]. Further analysis showed that student participation rates in online discussions, online learning, and online viewing of instructional videos were closely correlated with final grades in online courses (P < 0.01). In conclusion, our results suggest that the pedagogical effects of online education during COVID-19 were promising, and we provide a well-designed medical online course to inspire further improvements in online education.

In physical spaces, pointing interactions cannot rely on cursors, rays, or virtual hands for feedback as in virtual environments; users must rely solely on their perception and experience to capture targets. Currently, research on modeling target distribution for pointing interactions in physical space is relatively sparse. Area division is typically simplistic, and theoretical models are lacking. To address this issue, we propose two models for target distribution in physical space-pointing interactions: the single-target pointing endpoint distribution model (ST-PEDM) and the multi-target pointing endpoint distribution model (MT-PEDM). Based on these models, we have developed a basic region partitioning algorithm (BRPA) and an enhanced region partitioning algorithm (ERPA). We conducted experiments with 15 participants (11 males, and four females) to validate the proposed distribution models and region partitioning algorithm. The results indicate that these target distribution models accurately describe the distribution areas of targets, and the region partitioning algorithm demonstrates high precision and efficiency in determining user intentions during pointing interactions. At target distances of 200 cm and 300 cm, the accuracy without any algorithm is 60.54% and 42.39%, respectively. Using the BRPA algorithm, the accuracy is 72.94% and 68.57%, while, with the ERPA algorithm, the accuracy reaches 84.11% and 82.74%, respectively. This technology can be utilized in interaction scenarios involving handheld pointing devices, such as handheld remote controls. Additionally, it can be applied to the rapid capture control and trajectory planning of drone swarms. Users can quickly and accurately capture and control target drones using pointing interaction technology, issue commands, and transmit data through smart glasses, thereby achieving effective drone control and trajectory planning. [ABSTRACT FROM AUTHOR]

Natural rock fractures often exhibit non-matching characteristics at certain scales, leading to uneven aperture distributions that significantly affect fluid flow. This study investigates the impact of the mismatch between the upper and lower surfaces on the flow through three-dimensional rough fractures. By applying fractal theory, a rough upper surface of the fracture is generated, and different degrees of mismatch are introduced by adding random noise to this surface. This approach enables the construction of a variety of three-dimensional rough fracture flow models. Numerical simulations, which involve directly solving the Navier-Stokes equations, are used to simulate flow through a rough single fracture, assessing the effects of various degrees of mismatch between the surfaces. The study also examines how the inclusion of the matrix alters flow characteristics. The results demonstrate that the Forchheimer equation accurately describes the nonlinear flow behavior in fractures with different degrees of mismatch. The increased mismatch intensifies the uneven distribution of fracture apertures, causing the flow velocity to shift from uniform to discrete and the streamlines to become increasingly curved. The overall tortuosity of the flow path increases and the formation of 'concave' and 'convex' areas leads to vortex zones, promoting nonlinear seepage. The correlation between both viscous and inertial permeability with the degree of mismatch is negative, whereas the impact of matrix permeability on the flow capacity of the fracture shows a positive correlation with a mismatch. [ABSTRACT FROM AUTHOR]