Knowledge Transfer in Space Science

Knowledge Transfer (KT) is a major part of technical aspect in space science. By involving the research council funded Knowledge Transfer Account (KTA) programme and the university industrial and commercial partners, these strengthen the future research collaboration amongst the university, industrial, commercial, scientific and engineering communities. Since the space science research and development is a multi-billion pounds sterling industry, it is often referred as the most advanced research and technological breakthrough. The industry inventions including scratch-resistant lenses, smoke detectors, cordless tools, water filters become the popular industrial products. They benefit us enormously. This paper is to present the Future Universities and Future Knowledge Systems for KT in space science. It includes the discussion of the European Union (EU) Seventh Framework Programme (FP7) and its einfrastructure projects, Astrogrid Virtual Observatory, Gaia Data Centre, European Space Agency (ESA) XMMNewton Satellite Reflection Grating Spectrometer and Optical Monitor, National Aeronautics and Space Administration (NASA) Swift Explorer mission UltraViolet/Optical Telescope, Hinode Extreme UltraViolet (EUV) imaging spectrometer, Near Infrared Spectrograph (NIRSpec), Cassini Electron Spectrometer (ELS), CryoSat-2 mission simulation and EnviSat radar altimeter, GlobIce, SOHO, Cluster-2, ESA’s Exobiology on Mars (ExoMars) Panoramic Cameras (PanCam) and stereo mapping plus many future space missions in the pipeline. The United Kingdom (UK) Government’s Engineering Physical Science Research Council (EPSRC) and University College London (UCL) develop the programme of exchanging knowledge via their KTA. The account itself has a wide range of industrial and commercial partners. The aim of the programme is to attract the highly skilled people and the high-tech industries (such as space industry) to innovate and to develop the opportunities in the industrial/commercial fields and value added market. All these can be achieved with the collaboration and KT in the Future Universities and Future Knowledge System

Multi-Scale Representation and Recognition of Three Dimensional Surfaces Using Geometric Invariants

A novel technique for multi-scale representation and recognition of three-dimensional (3-D) surfaces is presented. This is achieved by iteratively convolving local parametrizations of the surface with two-dimensional (2-D) Gaussian filters. In this technique, semigeodesic coordinates are constructed such that each vertex of a mesh becomes a local origin. A geodesic line from the origin is first constructed in an arbitrary direction such as the direction of one of the incident edges. The smoothing process eliminates surface noise and small surface detail gradually, and results in simplification of the object shape. Using this technique the surface Gaussian curvature (K) and mean curvature (H) values are estimated accurately at multiple scales together with curvature zero crossing contours. Furthermore, local maxima of absolute values of K and H as well as the torsion local maxima of absolute values of the zero crossing contours of K and H are located on the surface. These features are utilized by geometric hashing and global verification processes for robust object recognition. The matching algorithm uses a hash table prepared in the off-line stage. Given a scene of feature points, the measurements taken at scene points are matched to those stored in the hash table. Recognition results are demonstrated for rotated and scaled as well as partially occluded objects. In order to verify matches, 3-D translation, rotation and scaling parameters are calculated and results indicate that the technique is invariant to those transformations. Another advantage is that it is applicable to both incomplete surfaces which arise during occlusion and to surfaces with holes

Viral loads in clinical specimens and SARS manifestations.

1. A high viral load in nasopharyngeal aspirate (with or without a high viral load in serum) is a useful prognostic indicator of respiratory failure or mortality. The presence of viral RNA in multiple body sites is also indicative of poor prognosis. 2. Early treatment with an effective antiviral agent before day 10 may decrease the peak viral load, and thus ameliorate the clinical symptoms and mortality, and reduce viral shedding and the risk of transmissionpublished_or_final_versio

Mixup for Test-Time Training

Test-time training provides a new approach solving the problem of domain shift. In its framework, a test-time training phase is inserted between training phase and test phase. During test-time training phase, usually parts of the model are updated with test sample(s). Then the updated model will be used in the test phase. However, utilizing test samples for test-time training has some limitations. Firstly, it will lead to overfitting to the test-time procedure thus hurt the performance on the main task. Besides, updating part of the model without changing other parts will induce a mismatch problem. Thus it is hard to perform better on the main task. To relieve above problems, we propose to use mixup in test-time training (MixTTT) which controls the change of model's parameters as well as completing the test-time procedure. We theoretically show its contribution in alleviating the mismatch problem of updated part and static part for the main task as a specific regularization effect for test-time training. MixTTT can be used as an add-on module in general test-time training based methods to further improve their performance. Experimental results show the effectiveness of our method.Comment: 11 page

Acupuncture transmitted infections.

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Persistence of hepatic hepatitis B virus after serological clearance of HBsAG with autologous peripheral stem cell transplantation

Delayed clearance of hepatitis B surface antigen was previously reported in a 38 year old woman after high dose chemotherapy with autologous peripheral blood stem cell rescue. Sixteen months later, this patient remained hepatitis B surface antigen negative, hepatitis B surface anti-body positive, and serum hepatitis B DNA negative by polymerase chain reaction. Serial liver biopsies (one at hepatitis B e antigen positive stage, one at hepatitis B e antibody positive stage, and one at hepatitis B surface antigen negative and hepatitis B surface antibody positive stage) showed a gradual resolution of the inflammatory activity with loss of hepatitis B e antigen and then hepatitis B surface antigen in the serum. However, the degree of fibrosis, though mild, remained the same. With the serological clearance of hepatitis B surface antigen, a small amount of hepatitis B virus DNA was still detectable in the nuclei of liver cells.published_or_final_versio

Dynamic Label Graph Matching for Unsupervised Video Re-identification

© 2017 IEEE. Label estimation is an important component in an unsupervised person re-identification (re-ID) system. This paper focuses on cross-camera label estimation, which can be subsequently used in feature learning to learn robust re-ID models. Specifically, we propose to construct a graph for samples in each camera, and then graph matching scheme is introduced for cross-camera labeling association. While labels directly output from existing graph matching methods may be noisy and inaccurate due to significant cross-camera variations, this paper propose a dynamic graph matching (DGM) method. DGM iteratively updates the image graph and the label estimation process by learning a better feature space with intermediate estimated labels. DGM is advantageous in two aspects: 1) the accuracy of estimated labels is improved significantly with the iterations; 2) DGM is robust to noisy initial training data. Extensive experiments conducted on three benchmarks including the large-scale MARS dataset show that DGM yields competitive performance to fully supervised baselines, and outperforms competing unsupervised learning methods.

Coronavirus HKU15 in respiratory tract of pigs and first discovery of coronavirus quasispecies in 5′-untranslated region

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Genome-wide association study of hepatocellular carcinoma in Southern Chinese patients with chronic hepatitis B virus infection

One of the most relevant risk factors for hepatocellular carcinoma (HCC) development is chronic hepatitis B virus (HBV) infection, but only a fraction of chronic HBV carriers develop HCC, indicating that complex interactions among viral, environmental and genetic factors lead to HCC in HBV-infected patients. So far, host genetic factors have incompletely been characterized. Therefore, we performed a genome-wide association (GWA) study in a Southern Chinese cohort consisting of 95 HBV-infected HCC patients (cases) and 97 HBV-infected patients without HCC (controls) using the Illumina Human610-Quad BeadChips. The top single nucleotide polymorphisms (SNPs) were then validated in an independent cohort of 500 cases and 728 controls. 4 SNPs (rs12682266, rs7821974, rs2275959, rs1573266) at chromosome 8p12 showed consistent association in both the GWA and replication phases (OR combined = 1.31-1.39; p combined = 2.71×10 -5-5.19×10 -4; PAR combined = 26-31%). We found a 2.3-kb expressed sequence tag (EST) in the region using in-silico data mining and verified the existence of the full-length EST experimentally. The expression level of the EST was significantly reduced in human HCC tumors in comparison to the corresponding non-tumorous liver tissues (P<0.001). Results from sequence analysis and in-vitro protein translation study suggest that the transcript might function as a long non-coding RNA. In summary, our study suggests that variations at chromosome 8p12 may promote HCC in patients with HBV. Further functional studies of this region may help understand HBV-associated hepatocarcinogenesis. © 2011 Chan et al.published_or_final_versio