Design of Immersed Tunnel and How We Research Submerged Floating Tunnel

This chapter begins with the discussion of the immersed tunnel design, concerning its reason of existence, historical review, general design, transverse and longitudinal design, the interaction, and the critical issues. The discussion is founded on the author’s 10 year experience in building the Hong Kong-Zhuhai-Macao Bridge (HZMB) immersed tunnel as a site design engineer. The experience of building immersed tunnel is transferable to build the submerged floating tunnel, which has never been built. In author’s opinion, the submerged floating tunnel (SFT) technique will be the next generation of IMT technique. In the second part of this chapter, the author proceeds to discuss the strategy of SFT research and the latest development in CCCC SFT Technical Joint Research Team

The design and simulation of an autonomous system for aircraft maintenance scheduling

International audienceOperational support is a key issue for aircraft maintenance, which aims to improve operational efficiency and reduce operating costs under the premise of ensuring flight safety. Although many works have emerged to achieve this aim, they mostly address the concept of maintenance systems, the relationship between stakeholders and the loop of maintenance information separately. Hence, the cooperation between stakeholders could be impeded especially when urgent decisions should be made, relying on historical data and real-time data. In this paper, we propose an innovative design of an autonomous system supporting the automatic decision-making for maintenance scheduling. The design starts from the proposition of the analysis framework, to concept formulation of the system, to information transitional level interface, and ends with an instance of system module interactions. The underlying architecture illustrates the high-level fusion of technical and business drives; optimizes strategies and plans with regard to maintenance costs, service level and reliability. An agent-based simulation system is developed as a proof to illustrate the feasibility of the system principle and algorithms. Furthermore, the simulation experiment analyzing the impact of maintenance sequence strategies on maintenance costs and service level has demonstrated the algorithm functionality and the feasibility of the proposed approach

Observations of Magnetic Helicity Proxies in Solar Photosphere: Helicity with Solar Cycles

Observations of magnetic helicity transportation through the solar photosphere reflect the interaction of turbulent plasma movements and magnetic fields in the solar dynamo process. In this chapter, we have reviewed the research process of magnetic helicity inferred from the observed solar magnetic fields in the photosphere and also the solar morphological configurations with solar cycles. After introducing some achievements in the study of magnetic helicity, some key points would like to be summarized. The magnetic (current) helicity in the solar surface layer presents a statistical distribution similar to that of the sunspot butterfly diagram, but its maximum value is delayed from the extreme value of the sunspot butterfly diagram and corresponds in the phase with the statistical eruption of solar flares. During the spatial transport of magnetic (current) helicity from the interior of the sun into the interplanetary space at the time-space scale of the solar cycle, it shows the statistical distribution and the fluctuation with the hemispheric sign rule. These show that the current helicity and magnetic helicity transport calculation methods are complementary to each other. We also notice that the study of the inherent relationship between magnetic helicity and the solar cycle still depends on the observed accuracy of the solar magnetic field.Comment: 48 page,17 figure

Learning to Expand: Reinforced Pseudo-relevance Feedback Selection for Information-seeking Conversations

Intelligent personal assistant systems for information-seeking conversations are increasingly popular in real-world applications, especially for e-commerce companies. With the development of research in such conversation systems, the pseudo-relevance feedback (PRF) has demonstrated its effectiveness in incorporating relevance signals from external documents. However, the existing studies are either based on heuristic rules or require heavy manual labeling. In this work, we treat the PRF selection as a learning task and proposed a reinforced learning based method that can be trained in an end-to-end manner without any human annotations. More specifically, we proposed a reinforced selector to extract useful PRF terms to enhance response candidates and a BERT based response ranker to rank the PRF-enhanced responses. The performance of the ranker serves as rewards to guide the selector to extract useful PRF terms, and thus boost the task performance. Extensive experiments on both standard benchmark and commercial datasets show the superiority of our reinforced PRF term selector compared with other potential soft or hard selection methods. Both qualitative case studies and quantitative analysis show that our model can not only select meaningful PRF terms to expand response candidates but also achieve the best results compared with all the baseline methods on a variety of evaluation metrics. We have also deployed our method on online production in an e-commerce company, which shows a significant improvement over the existing online ranking system

Superwettable PVDF/PVDF-g-PEGMA Ultrafiltration Membranes

Poly(vinylidene fluoride) (PVDF) is a common and inexpensive polymeric material used for membrane fabrication, but the inherent hydrophobicity of this polymer induces severe membranes fouling, which limits its applications and further developments. Herein, we prepared superwettable PVDF membranes by selecting suitable polymer concentration and blending with PVDF-graft-poly(ethylene glycol) methyl ether methacrylate (PVDF-g-PEGMA). This fascinating interfacial phenomenon causes the contact angle of water droplets to drop from the initial value of over 70° to virtually 0° in 0.5 s for the best fabricated membrane. The wetting properties of the membranes were studied by calculating the surface free energy by surface thermodynamic analysis, by evaluating the peak height ratio from Raman spectra, and other surface characterization methods. The superwettability phenomenon is the result of the synergetic effects of high surface free energy, the Wenzel model of wetting, and the crystalline phase of PVDF. Besides superwettability, the PVDF/PVDF-g-PEGMA membranes show great improvements in flux performance, sodium alginate (SA) rejection, and flux recovery upon fouling

Chondroprotective Activity of Murraya exotica

Osteoarthritis (OA) is a degenerative joint disease that affects millions of people. Currently, there is no effective drug treatment for it. The purpose of this study is to investigate the chondroprotective effects of Murraya exotica (L.) on OA. The rat OA models were duplicated to prepare for separating OA chondrocytes, synovial fluid (SF), and serum containing M. exotica (50 mg/kg, 100 mg/kg, and 200 mg/kg), M. exotica showed the activity of decreasing the contents of TNF-α and IL-1β in SF and the chondrocyte apoptosis in a dose-dependent manner. To investigate the probable mechanism, quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to determine gene expression and protein profiles, respectively. The results reveal that M. exotica can downregulate mRNA and protein expressions of β-catenin and COX-2 and reporter activity significantly. Conclusively, M. exotica exhibits antiapoptotic chondroprotective activity probably through inhibiting β-catenin signaling