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With the rapid development and construction of urban subways, various risks associated with human health and wellbeing within subway microenvironments have seriously increased. However, only a few intelligent systems have been validated as suitable for facilitating the management of subway environments. Field tests can be time-consuming and inefficient, and questionnaires often lack true intuitiveness for participants. Therefore, to enhance subway environment management, this study proposed intelligent systems that integrate building information modeling (BIM) and virtual reality (VR) for managing health risks in urban subway microenvironments. The systems were developed using Revit 2021, Navisworks 2020, Unity 2019, MYSQL 8.0, and Visual Studio 2019. Additionally, they were applied in scenarios for environmental assessment and passenger coping capability enhancement, differentiated into an expert visual-based health risk assessment system and a gamified simulation system for passenger risk prevention. The feasibility of the approach was validated with the case of Xinzhuang subway station of Line 3 in Nanjing, China. The findings revealed that the assessment system enabled experts to have a better and straight understanding of subway microenvironmental health risks and the gamification simulation system significantly enhanced the passengers' coping capacity. The integration of BIM and VR, with its design features such as visibility, optimization, and simulation, compensated for BIM's lack of providing an immersive experience for systems. The intelligent systems introduced in this study present novel models for environmental assessment and passenger training, catering to both subway operators and researchers. The innovative systems serve as a cornerstone in guaranteeing the health and safety of public transportation operations. [ABSTRACT FROM AUTHOR]

Integrating CO2 reduction with methanol oxidation presents a promising alternative strategy to store solar energy in CO2 reduction and produce more sustainable clean fuels and chemicals products, while identifying the carbon sources in the final products and elucidating the interactions between CO2 and methanol within such a mixed system is still particularly challenging. Herein, this study explores the efficiency of synergistic photocatalytic CO2 reduction and methanol oxidation via self-photogenerated oxygen vacancy-rich TiO2 nanostructures. Employing NMR spectroscopy and GC–MS analysis for 13CO2 isotope tracing samples, the exact carbon sources in both liquid and gas-phase products were clearly figure out. Moreover, through in situ DRIFTS analysis and DFT calculations, the crucial role of oxygen vacancies in enhancing catalytic activity and selectivity is revealed, and the CO2 reduction and methanol oxidation pathway on oxygen vacancy-rich TiO2 nanostructures are proposed. Consequently, our findings offer profound implications for advancing the field of synergistic photocatalytic processes, aiming to generate high-value chemical fuels sustainably. [ABSTRACT FROM AUTHOR]

The precise and prompt determination of quality control indicators such as moisture, stilbene glycosides, and anthraquinone glycosides is crucial in assessing the quality of Polygoni Multiflori Radix. Near-infrared spectroscopy is a nondestructive analytical technique that offers a more desirable approach than traditional methods for assessing content levels. In this study, various spectral preprocessing techniques were used to preprocess the raw spectral data. The spectral data were correlated with the determination of three-component contents using the partial least squares regression (PLSR) method. Then different algorithms, such as competitive adaptive weighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE), and random frog hopping (RF), were used for model simplification and feature selection. The data suggest that the first-order deconvolution derivative (1st Dev.) processing of the spectral data is superior to other methods in all three model evaluation metrics. The PLSR model for moisture, stilbene glycosides, and anthraquinone glycosides produced the calibration coefficient of determination (R2C) of 0.82, 0.52, and 0.58, the root mean square error of cross validation (RMSECV) of 0.91%, 0.77%, and 0.69%, the prediction coefficient of determination (R2P) of 0.72, 0.28, and 0.54, the root mean square error of prediction (RMSEP) of 0.65%, 0.81%, and 0.75%, and relative percentage differences (RPDs) of 1.7, 1.0, and 0.8. After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. This research provides a feasible method for rapid compliance testing of Polygoni Multiflori Radix. To further improve the model's performance and applicability, it is necessary to continuously expand the sample set with different varieties and locations for wide variation. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the short‐term (1 week after completion of treatment) effect of office‐based vergence and anti‐suppression therapy (OBVAT) on the Office Control Score when compared to observation alone in children with small‐to‐moderate angle intermittent exotropia (IXT). Methods: In this single‐masked (examiner masked), two‐arm, single‐centre randomised clinical trial, 40 participants, 6 to <18 years of age with untreated IXT, were randomly assigned to OBVAT or observation alone. Participants assigned to therapy received 60 min of OBVAT with home reinforcement once per week for 16 weeks. Therapy included vergence, accommodation and anti‐suppression techniques. The primary outcome measure was the comparison of the distance Office Control Score between the two groups at the primary outcome visit (i.e., 17‐week follow‐up visit). Results: At the primary outcome visit, the OBVAT group (n = 20) had a significantly better distance Office Control Score (adjusted mean difference: −0.9; 95% CI: −0.2 to −1.5; p = 0.008; partial eta squared: 0.19) than the observation group (n = 16). Participants from the OBVAT group were more likely than those from the observation group to have ≥1 point of improvement at the 17‐week visit (OBVAT group: 75%; Observation group: 25%; p = 0.006). Conclusions: In this randomised clinical trial of participants aged 6 to <18 years with IXT, we found that the OBVAT group had a significantly better distance Office Control Score than the observation group at the 17‐week visit. This study provides the first data from a randomised clinical trial demonstrating the effectiveness of OBVAT for improving the control of IXT. Eye care practitioners should consider OBVAT as a viable, non‐surgical treatment option for IXT. A full‐scale randomised clinical trial investigating the long‐term effectiveness of OBVAT in treating IXT is warranted. [ABSTRACT FROM AUTHOR]