Vibration prediction and analysis of the main beam of the TBM based on a multiple linear regression model.

The vibration of tunnel boring machine (TBM) is very difficult to monitor on sites, and related research on prediction methods is rare. Based on the field tunnelling test of a TBM in the Xinjiang Ehe project, the vibration information of the main beam of the TBM under different surrounding rock conditions is collected. The relationships among the tunnelling parameters, surrounding rock parameters and vibration parameters were studied. The results show that the penetration, cutter head speed, torque and thrust are important parameters affecting TBM vibration. In addition, the field penetration index and cutter head driving power index are significantly related to the root mean square of acceleration. Based on this, a multiple regression prediction model of TBM vibration is established. The model was verified and analysed via field projects, and the relative prediction error was less than 12%. This method can be used to predict the vibration of a TBM in real time through characteristic parameters without the use of a traditional monitoring system. This approach is highly important for determining the status of TBM equipment in real time.

Research on prevention and control technology of classified rockburst in TBM construction of deeply buried tunnels.

Rock blasting and other geological disasters occur frequently in the TBM construction of deeply buried tunnels and seriously threaten construction safety and progress. Therefore, it is extremely important to conduct scientific research for effective prevention and control of rockbursts in construction. Based on a large number of field rockburst data, this study analyses the influence of rockburst on construction safety and efficiency by using statistical theory and summarizes the temporal and spatial characteristics of rockburst time, location and influence range. Using these results, combined with the characteristics of the TBM structure and construction method, classification prevention and control objectives, theoretical criteria and prevention and control technology of rock bursts are proposed. A theoretical system of classified prevention and control of rockburst is constructed, which is cooperatively controlled by microseismic monitoring, TBM equipment, TBM excavation and support measures. The system is verified to provide practical protection, demonstrating that this report provides an important reference for the prevention and control of rock bursts in ultradeep tunnels.

Automatic detection of myocardial ischaemia using generalisable spatio-temporal hierarchical Bayesian modelling of DCE-MRI.

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) can be used as a non-invasive method for the assessment of myocardial perfusion. The acquired images can be utilised to analyse the spatial extent and severity of myocardial ischaemia (regions with impaired microvascular blood flow). In the present paper, we propose a novel generalisable spatio-temporal hierarchical Bayesian model (GST-HBM) to automate the detection of ischaemic lesions and improve the in silico prediction accuracy by systematically integrating spatio-temporal context information. We present a computational inference procedure with an adequate trade-off between accuracy and computational efficiency, whereby model parameters are sampled from the posterior distribution with Gibbs sampling, while lower-level hyperparameters are selected using model selection strategies based on the Watanabe Akaike information criterion (WAIC). We have assessed our method on both synthetic (in silico) data with known gold-standard and 12 sets of clinical first-pass myocardial perfusion DCE-MRI datasets. We have also carried out a comparative performance evaluation with four established alternative methods: Gaussian mixture model (GMM), opening and closing operations based on Gaussian mixture model (GMMC&Omax), Markov random field constrained Gaussian mixture model (GMM-MRF) and model-based hierarchical Bayesian model (M-HBM). Our results show that the proposed GST-HBM method achieves much higher in silico prediction accuracy than the established alternative methods. Furthermore, this method appears to provide a more robust delineation of ischaemic lesions in datasets affected by spatially variant noise.

Human mesenchymal stem cells derived from adipose tissue showed a more robust effect than those from the umbilical cord in promoting corneal graft survival by suppressing lymphangiogenesis.

BACKGROUND: Mesenchymal stem cells (MSCs) have shown promising potential in allograft survival. However, few reports have focused on comparing the immunosuppressive capacity of MSCs from different sources and administered via different routes in inhibiting transplant rejection. Moreover, virtually nothing is known about the role of MSCs in the regulation of graft neovascularization and lymphangiogenesis. In this study, we compared the efficacy of human adipose MSCs (hAD-MSCs) and human umbilical cord MSCs (hUC-MSCs) in vitro and in corneal transplantation models to explore the underlying molecular mechanisms and provide a powerful strategy for future clinical applications. METHODS: hAD-MSCs and hUC-MSCs were generated, and their self-renewal and multi-differentiation abilities were evaluated. The inhibitory effect of human MSCs (hMSCs) was examined by T-cell proliferation assays with or without transwell in vitro. Two MSCs from different sources were separately adoptively transferred in mice corneal transplantation (5 × 105 or 1 × 106/mouse) via topical subconjunctival or intravenous (IV) routes. Allograft survival was evaluated every other day, and angiogenesis and lymphomagenesis were quantitatively analyzed by immunofluorescence staining. The RNA expression profiles of hMSCs were revealed by RNA sequencing (RNA-seq) and verified by quantitative real-time PCR (qRT‒PCR), western blotting or ELISA. The function of the differentially expressed gene FAS was verified by a T-cell apoptosis assay. RESULTS: hAD-MSCs induced stronger immunosuppression in vitro than hUC-MSCs. The inhibitory effect of hUC-MSCs but not hAD-MSCs was mediated by cell-cell contact-dependent mechanisms. Systemic administration of a lower dose of hAD-MSCs showed better performance in prolonging corneal allograft survival than hUC-MSCs, while subconjunctival administration of hMSCs was safer and further prolonged corneal allograft survival. Both types of hMSCs could inhibit corneal neovascularization, while hAD-MSCs showed greater superiority in suppressing graft lymphangiogenesis. RNA-seq analysis and confirmation experiments revealed the superior performance of hAD-MSCs in allografts based on the lower expression of vascular endothelial growth factor C (VEGF-C) and higher expression of FAS. CONCLUSIONS: The remarkable inhibitory effects on angiogenesis/lymphangiogenesis and immunological transplantation effects support the development of hAD-MSCs as a cell therapy against corneal transplant rejection. Topical administration of hMSCs was a safer and more effective route for application than systemic administration.

Performance optimization of aircraft deicing equipment based on genetic algorithm.

Using deicing fluids is the main way of aircraft ground deicing, which plays an important role in ensuring flights' safety. However, most of the airports use deicing fluids excessively to ensure the quality and efficiency of aircraft ground deicing, which will not only cause a large amount of deicing fluids wasted but also pollute water resources and the environment. Finding the optimal solution between deicing efficiency and deicing fluids consumption through effective methods is necessary. This article analyzes the energy conversion process of aircraft ground deicing, establishes multi-parameter optimization model for deicing, and optimizes the consumption of deicing fluids. The physical quantity, including the flow rate and the temperature of deicing fluids, is found as the main influence of the deicing time, which is the most concerned problem in the actual operation. Under the precondition of ensuring the deicing efficiency, the optimized parameters such as different ambient temperature, wing area, and icing thickness are obtained by genetic algorithm. The trend between the parameters with the change of environment has also been analyzed. Finally, the actual using condition in the capital airport and the optimized results are compared, and the results show that the usage of deicing fluids reduced 13% to 24%.