COVID-19 and Virtual Nutrition: A Pilot Study of Integrating Digital Food Models for Interactive Portion Size Education.

Background and aims: Digital food viewing is a vital skill for connecting dieticians to e-health. The aim of this study was to integrate a novel pedagogical framework that combines interactive three- (3-D) and two-dimensional (2-D) food models into a formal dietetic training course. The level of agreement between the digital food models (first semester) and the effectiveness of educational integration of digital food models during the school closure due to coronavirus disease 2019 (COVID-19) (second semester) were evaluated. Method: In total, 65 second-year undergraduate dietetic students were enrolled in a nutritional practicum course at the School of Nutrition and Health Sciences, Taipei Medical University (Taipei, Taiwan). A 3-D food model was created using Agisoft Metashape. Students' digital food viewing skills and receptiveness towards integrating digital food models were evaluated. Results: In the first semester, no statistical differences were observed between 2-D and 3-D food viewing skills in food identification (2-D: 89% vs. 3-D: 85%) and quantification (within ±10% difference in total calories) (2-D: 19.4% vs. 3-D: 19.3%). A Spearman correlation analysis showed moderate to strong correlations of estimated total calories (0.69~0.93; all p values < 0.05) between the 3-D and 2-D models. Further analysis showed that students who struggled to master both 2-D and 3-D food viewing skills had lower estimation accuracies than those who did not (equal performers: 28% vs. unequal performers:16%, p = 0.041), and interactive 3-D models may help them perform better than 2-D models. In the second semester, the digital food viewing skills significantly improved (food identification: 91.5% and quantification: 42.9%) even for those students who struggled to perform digital food viewing skills equally in the first semester (equal performers: 44% vs. unequal performers: 40%). Conclusion: Although repeated training greatly enhanced students' digital food viewing skills, a tailored training program may be needed to master 2-D and 3-D digital food viewing skills. Future study is needed to evaluate the effectiveness of digital food models for future "eHealth" care.

Orthogonal incidence method for efficient sunlight collection from asymmetric light couplers in tree-structured light guiding systems.

Directly transporting sunlight for use in indoor lighting applications is an efficient way to utilize solar energy. This study proposes a tree-structured light guiding system (TLGS) to collect sunlight and transport it for indoor illumination. The use of asymmetric light couplers in a TLGS increases the amount of accumulated sunlight. An analytic ray tracing model of the asymmetric coupler is proposed to present the angle and height distributions of the propagated rays. The cutoff angles were derived, and this cutoff condition was used to determine which rays are able to travel through the coupling region. In simulations, the couplers with coupling angles (θ(coup)) of 30° and 50° were conducted, and the large θ(coup) coupler provided high coupling efficiency (0.450). The orthogonal incidence method was adopted to increase coupling efficiency (0.646), and subsequently the amount of accumulated sunlight. The amount of accumulated sunlight in a TLGS was increased by 44%.