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Introduction: The COVID-19 pandemic in the past few years led to major adjustments in the provision of healthcare. This study aimed to investigate trainees' perception of impact of the pandemic on specialty training in Obstetrics & Gynaecology (O&G) in Hong Kong. Methods: A cross-sectional questionnaire survey was performed on all the O&G trainees and the young fellows of the Hong Kong College of Obstetricians and Gynaecologists (HKCOG). The questionnaires included 5 parts: demographic data, impact on clinical activities, redeployment, educational activities and career progression. Results: A total of 104 questionnaires (92.9%) were received for final analysis. The majority of the participants had reductions in elective and emergency operations, as well as exposure to in-patient admissions and out-patient clinics in both obstetrics and gynaecology. The reduction was most significant in elective gynaecology operations. One-third (34.6%) of the participants had been redeployed to other departments, and educational activities were reduced during the pandemic. Around 58% of the trainees were concerned with the reduction in clinical exposure, and 78% worried they would not be able to log sufficient number of surgical procedures. Basic trainees were significantly more worried than higher trainees. Around half of the trainees had doubts or regrets about choosing to undergo O&G specialty training. Conclusion: The O&G trainees in Hong Kong perceived that the COVID-19 pandemic had significant negative impacts on their training. Many trainees were worried they would not be able to attain the required level of competence when they complete their specialist training. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the local incidence of orofacial cleft (OFC) encountered in fetal morphology scan and prenatal diagnosis, genetic etiology of fetuses with or without other structural abnormalities, and their pregnancy outcomes. Design: Retrospective cohort study. Setting: Two maternal fetal medicine units, tertiary hospitals, Hong Kong. Participants: All pregnant women with antenatal diagnosis of fetal OFC between January 2016 and December 2020 (N = 66). Results: OFC has an incidence of 0.13% among pregnancies in Hong Kong and 28.8% (19/66) were syndromic cleft that exhibited other fetal structural anomalies. There were 55 cases (84.6%) who opted for invasive prenatal diagnostic testing. Genetic defects were identified in 25.8% (17/66) of this cohort, including 14 pathogenic variants. The detection rate in the syndromic cases is 68.4% (13/19) which was significantly higher than 8.5% (4/47) among non-syndromic cases. Aneuploidies would be the most common cause, accounting for 9.1% (6/66). Chromosomal microarray analysis (CMA) provided an incremental diagnostic yield of 6.1% compared to conventional karyotyping. A total of 29 live births including 3 cases of a variant of uncertain significance and 26 cases without genetic abnormalities detected have continued pregnancy to birth. There were 87.5% (21/24) without detectable pathogenic genetic abnormality reported good long-term outcomes. The chance of OFC fetuses having a good long-term outcome was significantly higher if no genomic variant was detected (P <.001). Conclusions: Invasive prenatal tests with CMA should be offered to pregnancies with OFC regardless of the type. It has provided incremental diagnostic yield over conventional karyotyping and helped in prenatal and genetic counseling. A negative result in non-syndromic OFC favors couples to keep the pregnancy. [ABSTRACT FROM AUTHOR]

Background/Purpose: This is a local retrospective review on the outcomes of tenolysis after phalangeal fracture. Methods: The clinical outcome of nine patients (mean age 51.9 years) with finger fractures and subsequent tenolysis performed were reviewed. Range of motion was evaluated. Results: Extensor tenolysis, capsulotomy with or without flexor tenolysis was performed at a mean of 8.2 months after hand fracture with fracture fixation done. The total active motion (TAM) improved from 121° preoperatively to 173° postoperatively (p = 0.02). Significant improvement of motion was observed at the proximal interphalangeal joint (p = 0.012). All patient's range of motion improved after surgery. Conclusion: The gain of motion of 52° is comparable to other series. Release of all pathological anatomy and aggressive mobilization may improve the result further. Tenolysis can provide an encouraging improvement of active motion for stiff finger after phalangeal fractures. Recent results using WALANT technique showed satisfactory outcome. Future study on WALANT technique may further consolidate its potential benefit. [ABSTRACT FROM AUTHOR]

As the first waterproof component of the immersed tunnel, it is very important to ensure the remaining compression of the GINA gasket to resist external water intrusion. This paper proposed a method for determining warning thresholds for the remaining compression of the GINA gasket based on a material-to-mechanical analysis. In terms of material analysis, two factors that affect the GINA gasket are investigated: rubber hardness and cross-sectional shape, and they are adopted as the basis for subsequent mechanical analysis. In terms of mechanical analysis, uneven settlement during the operation period is considered to be the major cause of joint deformation, which is further divided into four modes: bending, shear, expansion, and torsion, with the computation model of the GINA gasket established to obtain the warning threshold. After that, a graded early warning method is adopted, and corresponding thresholds are given after an investigation of previous studies, which are validated by a three-dimensional finite element analysis. The deformation monitoring data between the E28 and E29 elements of the Hong Kong–Zhuhai–Macao Bridge Immersed Tunnel are used to verify the proposed method. The results show that the GINA gasket of the Hong Kong–Zhuhai–Macao Bridge Immersed Tunnel is currently in a safe state, and its deformation is much lower than the minimum warning level. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) is gradually replacing traditional manual detection and is becoming a focus of the research devoted to the operation and maintenance of tunnel structures. However, in the face of massive SHM data, the autonomous early warning method is still required to further reduce the burden of manual analysis. Thus, this study proposed a dynamic warning method for SHM data based on ARIMA and applied it to the concrete strain data of the Hong Kong–Zhuhai–Macao Bridge (HZMB) immersed tunnel. First, wavelet threshold denoising was applied to filter noise from the SHM data. Then, the feasibility and accuracy of establishing an ARIMA model were verified, and it was adopted to predict future time series of SHM data. After that, an anomaly detection scheme was proposed based on the dynamic model and dynamic threshold value, which set the confidence interval of detected anomalies based on the statistical characteristics of the historical series. Finally, a hierarchical warning system was defined to classify anomalies according to their detection threshold and enable hierarchical treatments. The illustrative example of the HZMB immersed tunnel verified that a three-level (5.5 σ, 6.5 σ, and 7.5 σ) dynamic warning schematic can give good results of anomalies detection and greatly improves the efficiency of SHM data management of the tunnel. [ABSTRACT FROM AUTHOR]

• The flood disasters under the compound effects of rain-tide-wind for artificial islands are analyzed. • The extreme compound scenario have a low probability but may cause serious flooding on artificial islands. • The contributing flooding factors for the artificial island are wave overtopping and rainfall. • Wave overtopping induced by high wind speeds and tide levels exacerbate flooding. • The flooding risk assessment for cars on the island is assessed for compound scenarios. Tropical cyclones are often accompanied by heavy rainfall, high tides, and strong wind speeds, which can induce serious compound floods resulting in immeasurable losses to coastal areas. Studies on flood risk for ocean engineering by compound impacts of rain, tide, and wind are still limited to date. The west artificial island of Hong Kong-Zhuhai-Macao Bridge is a vital link between the immersed tunnel and the bridge. The flooding on the artificial island under the compound effects of rain-tide-wind and the flood risk of cars were analyzed in this study. We propose rain-tide-wind joint probabilities for different compound scenarios based on historical observational data of tropical cyclones. The artificial island hydrodynamic model was created to evaluate flood disasters induced by rainfall and wave overtopping. The 24-hour flood process and maximum flood depth distribution of each scenario are presented. The car damage in floods by the compound effects was assessed to derive the probability-car damage curve for risk assessment. The study provides technical support for artificial island flood prevention and disaster risk reduction. [ABSTRACT FROM AUTHOR]

In order to predict the joint opening-closing deformation of immersed tunnel in operation, a comprehensive prediction model combining time series decomposition, least square method, sparrow search algorithm (SSA) and support vector regression (SVR) is proposed, which is verified by the monitoring data of E13-E14 and E17-E18 joints opening-closing deformation of immersed tunnel in Hong Kong-Zhuhai-Macao Bridge. Firstly, on the basis of summarizing and analyzing the characteristics of joint opening-closing deformation, the monitoring sequence of joint opening-closing is decomposed into trend component, periodic component and residual component by using time series decomposition singular spectrum analysis method, which clearly shows the composition of each component. Secondly, the least square method is used to fit and predict the trend component; Combining the commonly used RBF kernel function, Sigmoid kernel function and Ploy kernel function with SVR respectively, the SSA algorithm is used to globally optimize the penalty factors and kernel function parameters of the three models, and the optimized three coupling models are used to predict the periodic component and residual component. The results show that the prediction effect of the SVR model optimized by SSA algorithm is better than that of the traditional SVR model, The prediction result of SSA-SVR model constructed by RBF kernel function is the best. Finally, the time series addition model is applied to superimpose the optimal predicted values to obtain the predicted opening-closing amount. The mean square errors of the total predicted values of the opening-closing amount of the two joints are 0.1900mm and 0.2291mm respectively, the average errors are 0.1587mm and 0.2156mm respectively, and the correlation coefficients are 0.9792 and 0.9695 respectively. A satisfactory prediction effect is obtained, which proves the reliability and accuracy of this method, and provides a new way for the prediction of the opening-closing deformation of the pipe joint of immersed tunnel during the operation period. [ABSTRACT FROM AUTHOR]