Rapid Estimation of Binding Activity of Influenza Virus Hemagglutinin to Human and Avian Receptors

A critical step for avian influenza viruses to infect human hosts and cause epidemics or pandemics is acquisition of the ability of the viral hemagglutinin (HA) to bind to human receptors. However, current global influenza surveillance does not monitor HA binding specificity due to a lack of rapid and reliable assays. Here we report a computational method that uses an effective scoring function to quantify HA-receptor binding activities with high accuracy and speed. Application of this method reveals receptor specificity changes and its temporal relationship with antigenicity changes during the evolution of human H3N2 viruses. The method predicts that two amino acid differences at 222 and 225 between HAs of A/Fujian/411/02 and A/Panama/2007/99 viruses account for their differences in binding to both avian and human receptors; this prediction was verified experimentally. The new computational method could provide an urgently needed tool for rapid and large-scale analysis of HA receptor specificities for global influenza surveillance.National Key Project (2008ZX10004-013)National Institutes of Health (U.S.) (grant AI07443)Singapore-MIT Alliance for Research and TechnologyMassachusetts Institute of Technology. International Science and Technology Initiatives Global Seed FundNational Basic Research Program (973 Program) (2009CB918503)National Basic Research Program (973 Program) (2006CB911002

10-qubit entanglement and parallel logic operations with a superconducting circuit

Here we report on the production and tomography of genuinely entangled Greenberger-Horne-Zeilinger states with up to 10 qubits connecting to a bus resonator in a superconducting circuit, where the resonator-mediated qubit-qubit interactions are used to controllably entangle multiple qubits and to operate on different pairs of qubits in parallel. The resulting 10-qubit density matrix is unambiguously probed, with a fidelity of $0.668 \pm 0.025$. Our results demonstrate the largest entanglement created so far in solid-state architectures, and pave the way to large-scale quantum computation.Comment: Revised version with 16 pages, 13 figures, and 2 table

Raman spectroscopic studies of carbon nanotube composite fibres

The project has been concerned with structure/property relationships in a series of different carbon nanotube (CNT) composite fibres. Raman spectroscopy has been proved to be a powerful technique to characterise the CNT-containing fibres. Electrospinning has been used to prepare poly(vinyl alcohol) (PVA) nanofibres containing single-wall carbon nanotubes (SWNTs). The effect of the processing conditions including the polymer concentration, electric voltage, tip-to-collector distance, nanotube concentration and the collection method upon the morphology, diameter and the alignment of the fibres have been investigated.Raman spectroscopy of individual SWNTs dispersed in PVA electrospun fibres have been studied systematically in terms of the Raman band frequency, intensity and linewidth. The G'-band shift per unit strain during tensile deformation has been found to be dependent on the nanotube chirality. A detailed study has been undertaken of the efficiency of reinforcement in PVA/SWNT nanocomposites. The stress-induced Raman band shifts in the nanocomposites have been shown to be controlled by both geometric factors such as the angles between the nanotube axis, the stressing direction and the direction of laser polarisation, and by finite length effects and bundling. A theory has been developed that takes into account all of these factors and enables the behavior of the different forms of nanocomposite, both fibres and films, to be compared.The effects of dispersion and orientation of nanotubes and the interfacial adhesion on mechanical properties of poly(p-phenylene terephthalamide) (PPTA)/SWNTs composite fibres have been investigated. It has been shown the change of orientation of the polymer molecules upon incorporating nanotubes had direct effect on mechanical properties of the PPTA fibres. An in-situ Raman spectroscopy study during fibre deformation has revealed good stress transfer from the matrix to nanotubes in low strain range, and the interface failed when the strain exceeded 0.5%.Raman spectroscopy has also been employed to investigate the microstructure and micromechanical process of neat carbon nanotube (CNT) fibres. It has been found the fibres consisted of both SWNTs and MWNTs and varied in composition at different locations. High efficiency of stress transfer both within the fibre and in composites has been observed, suggesting the promising potential of CNT fibres in reinforcing polymers.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Supercapacitance from cellulose and carbon nanotube nanocomposite fibers

Copyright © 2013 American Chemical SocietyACS AuthorChoice open access articleMultiwalled carbon nanotube (MWNT)/cellulose composite nanofibers have been prepared by electrospinning a MWNT/cellulose acetate blend solution followed by deacetylation. These composite nanofibers were then used as precursors for carbon nanofibers (CNFs). The effect of nanotubes on the stabilization of the precursor and microstructure of the resultant CNFs were investigated using thermogravimetric analysis, transmission electron microscopy and Raman spectroscopy. It is demonstrated that the incorporated MWNTs reduce the activation energy of the oxidative stabilization of cellulose nanofibers from 230 to 180 kJ mol–1. They also increase the crystallite size, structural order, and electrical conductivity of the activated CNFs (ACNFs). The surface area of the ACNFs increased upon addition of nanotubes which protrude from the fiber leading to a rougher surface. The ACNFs were used as the electrodes of a supercapacitor. The electrochemical capacitance of the ACNF derived from pure cellulose nanofibers is demonstrated to be 105 F g–1 at a current density of 10 A g–1, which increases to 145 F g–1 upon the addition of 6% of MWNTs.The authors would like to thank the [Engineering and Physical Sciences Research Council] EPSRC (EP/F036914/1 and EP/I023879/1), Guangdong and Shenzhen Innovative Research Team Program (No. 2011D052,KYPT20121228160843692), National Natural Science Foundation of China (Grant No. 21201175), R&D Funds for basic Research Program of Shenzhen (Grant No. JCYJ20120615140007998), and the Universities of Exeter and Manchester for funding this research

Effect of space flight factors on alfalfa seeds

To explore the effect of space flight factors on the early development of alfalfa seedling, dry seeds were placed onboard a satellite for a 15-day flight. After retrieval, the ultra structure of seed coat and the chemical content of seed were tested, followed by tests for germinate ability, seedling growth, and mitotic and chromosome aberrations. Results showed that space flight factors have both positive and negative effects on alfalfa seeds. Positive effects include: (1) A 6.2% increase in germinate potential and (2) an 80% decrease in the number of hard seed in flight seeds. Meanwhile, negative effects included a decrease of 3.0 and 33.2% in the index of germination and vigor of flight seeds, respectively, which may be partly due to the inhibition of cell mitotic (26% less than ground control) and root growth (29.0% less than ground control) after the space flight. Moreover, the DNA and Ca2+ content of alfalfa seeds increased after the space flight, while the reserve energy content of alfalfa seeds, such as saccharine and fatty acid, decreased after the space flight. Conclusively, space flight factors accelerate the germination process of alfalfa seeds but restrain the root from growing due to chromosomal damage and abnormal mitosis induced by cosmic radiation.Key words: Alfalfa, space flight factors, germination, chromosome aberration

Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory

Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. However, the heavy dependency on a large number of training data with dense annotation and the sensitiveness to the variation of data distribution severely restrict the potential application of DCNNs for the semantic segmentation of HRS imagery. This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery. MemoryAdaptNet constructs an output space adversarial learning scheme to bridge the domain distribution discrepancy between source domain and target domain and to narrow the influence of domain shift. Specifically, we embed an invariant feature memory module to store invariant domain-level context information because the features obtained from adversarial learning only tend to represent the variant feature of current limited inputs. This module is integrated by a category attention-driven invariant domain-level context aggregation module to current pseudo invariant feature for further augmenting the pixel representations. An entropy-based pseudo label filtering strategy is used to update the memory module with high-confident pseudo invariant feature of current target images. Extensive experiments under three cross-domain tasks indicate that our proposed MemoryAdaptNet is remarkably superior to the state-of-the-art methods.Comment: 17 pages, 12 figures and 8 table

N-doped porous carbon nanofibers embedded with TiN nanoparticles for high-performance Li–S batteries

Flexible N-doped porous carbon nanofibers embedded with TiN nanoparticles are prepared for cathode materials of lithium–sulfur (Li–S) batteries. A synergistic adsorption effect of lithium polysulfides (LiPSs) can be provided by the well-dispersed TiN nanoparticles, the heteroatomic doping, and the porous nanofibers structure. As a result, the as-prepared electrode can deliver a high reversible capacity of 990 mAh g−1 after 120 cycles at 0.2 A g−1 with coulombic efficiency approaching 100%. This work provides a simple and comprehensive strategy for the preparation of high-performance Li–S batteries.</p