Objective To provide a comprehensive and systematic analysis of demographic characteristics, clinical symptoms, laboratory findings and imaging features of coronavirus disease 2019 (COVID‐19) in pediatric patients. Methods A meta‐analysis was carried out to identify studies on COVID‐19 from December 25, 2019 to April 30, 2020. Results A total of 48 studies with 5829 pediatric patients were included. Children at all ages were at risk for COVID‐19. The main illness classification ranged as: 20% (95% CI: 14 to 26%, I 2 =91.4%) asymptomatic, 33% (95% CI: 23 to 43%, I 2 =95.6%) mild and 51% (95% CI: 42 to 61%, I 2 =93.4%) moderate. The typical clinical manifestations were fever 51% (95% CI: 45 to 57%, I 2 =78.9%) and cough 41% (95% CI: 35 to 47%, I 2 =81.0%). The common laboratory findings were normal white blood cell 69% (95% CI: 64 to 75%, I 2 =58.5%), lymphopenia 16% (95% CI: 11 to 21%, I 2 =76.9%) and elevated creatine‐kinase MB (CK‐MB) 37% (95% CI: 25 to 48%, I 2 =59.0%). The frequent imaging features were normal images 41% (95% CI: 30 to 52%, I 2 =93.4%) and ground‐glass opacity 36% (95% CI: 25 to 47%, I 2 =92.9%). Among children under 1‐year old, critical cases account for 14% (95% CI: 13 to 34%, I 2 =37.3%) that should be of concern. In addition, vomiting occurred in 33% (95% CI: 18 to 67%, I 2 =0.0%) cases that may also need attention. Conclusions Pediatric patients with COVID‐19 may experience milder illness with atypical clinical manifestations and rare lymphopenia. High incidence of critical illness and vomiting symptoms reward attention in children under 1‐year old. This article is protected by copyright. All rights reserved.

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Typhoon Megi passed between two subsurface moorings in the northern South China Sea in October 2010 and the upper ocean thermal and dynamical response with strong internal tides present was examined in detail. The entire observed water column (60-360 m) was cooled due to strong Ekmanpumped upwelling (up to 50 m in the thermocline) by Megi, with maximum cooling of 4.2 C occurring in thermocline. A relatively weak (maximum amplitude of 0.4 m s 21 ) and quickly damped (e-folding time scale of 2 inertial periods) near-inertial oscillation (NIO) was observed in the mixed layer. Power spectrum and wavelet analyses both indicated an energy peak appearing at exactly the sum frequency fD1 (with maximum amplitude up to 0.2 m s 21 ) of NIO (f) and diurnal tide (D1), indicating enhanced nonlinear wave-wave interaction between f and D1 during and after typhoon. Numerical experiments suggested that energy transfer from NIO to fD1 via nonlinear interaction between f and D1 may have limited the growth and accelerated the damping of mixed layer NIO generated by Megi. The occurrence of fD1 had a high correlation with NIO; the vertical nonlinear momentum term, associated with the vertical shear of NIO and vertical velocity of D1 or vertical shear of D1 and vertical velocity of NIO, was more than 10 times larger than the horizontal terms and was responsible for forcing fD1. After Megi, surface-layer diurnal energy was enhanced by up to 100%, attributed to the combined effect of the increased surface-layer stratification and additional Megi-forced diurnal current.

Much of the information stored on the web contains geographical context, but current search engines treat such context in the same way as all other content. In this paper the design, implementation and evaluation of a spatially-aware search engine are described which is capable of handling queries in the form of the triplet of . The process of identifying geographic references in documents and assigning appropriate footprints to documents, to be stored together with document terms in an appropriate indexing structure allowing real-time search is described. Methods allowing users to query and explore results which have been relevance ranked in terms of both thematic and spatial relevance have been implanted and a usability study indicates that users are happy with the range of spatial relationships available and intuitively understand how to use such a search engine. Normalised precision for 38 queries, containing four types of spatial relationships is significantly higher (p < 0.001) for search exploiting spatial information than pure text search.