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Background To detect various indicators of retinal vascular plexus through optical coherence tomography angiography (OCTA) in non-diabetics and diabetics at various stages, and to analyze the characteristics of retinal microcirculation during each stage of diabetes. Methods OCTA was used to detect the four groups, namely non-diabetic, non-diabetic retinopathy (NDR), non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR). Furthermore, it was also used to measure the retinal vascular density (VD) of the fovea, parafovea, and perifovea areas of the superficial capillary plexus (SCP) and deep capillary plexus (DCP). Results The logarithm of the minimum angle of resolution (LogMAR) visual acuity of the four groups of patients revealed a gradual upward trend, and a significant statistical difference (P < 0.001). The VD of Whole, Parafovea and Perifovea of SCP and DCP were compared between the control group, NDR group, NPDR group and PDR group, respectively, and the differences were statistically significant (P < 0.001). There was no significant difference in VD between the SCP and DCP of the fovea in the four groups (P > 0.001). The whole blood vessel density of the superficial retina and deep retina was significantly negatively correlated with LogMAR visual acuity (P < 0.001); There was no significant correlation observed between the superficial and deep fovea VD and LogMAR vision (P > 0.001). The superficial and deep parafovea VD exhibited a significant negative correlation with LogMAR vision (P < 0.001). The superficial and deep perifovea VD was significantly negatively correlated with LogMAR visual acuity (P < 0.001). Conclusion OCTA is a potential non-invasive imaging tool that can assist in monitoring the development of diabetic retinopathy, and the longer the disease period, the more obvious the decrease of retinal VD in patients.

The Hong Kong-Zhuhai-Macao Bridge (HZMB) is an important transportation facility connecting Hong Kong, Zhuhai, and Macao. Thus, analyzing the characteristics of cross-border behavior becomes crucial for enhancing the smart travel experience of the HZMB. Discrete choice models (e.g., logit models) are commonly used to describe travel mode choice behavior. Multinomial logit (MNL) is subjected to the independence of irrelevant alternatives (IIA) assumption. Nested logit (NL) model does not consider the heterogeneity of travel individuals. Mixed logit (MXL) model can overcome the above limitations, but it may neglect model uncertainty. Therefore, a Bayesian model averaging (BMA) approach is applied to model travel mode choice behavior considering using revealed preference/stated preference (RP/SP) fusion data collected by questionnaires online. A structural equation model (SEM) is adopted to explore the potential relationship between latent variables, and two travel modes (i.e., cross-border bus and cross-border private car) are selected to analyze the cross-border travel mode choice of the HZMB. The results reveal that the MXL-BMA approach can better explain the cross-border travel mode choice behavior. And the transportation modes arriving and departing the HZMB have a significant impact on the travel mode choice of the HZMB. The findings of this study can provide suggestions for designing personalized travel services for travelers across the HZMB.