SSA-SiamNet:Spectral-Spatial-Wise Attention-Based Siamese Network for Hyperspectral Image Change Detection

Deep learning methods, especially convolutional neural network (CNN)-based methods, have shown promising performance for hyperspectral image (HSI) change detection (CD). It is acknowledged widely that different spectral channels and spatial locations in input image patches may contribute differently to CD. However, they are treated equally in existing CNN-based approaches. To increase the accuracy of HSI CD, we propose an end-to-end Siamese CNN (SiamNet) with a spectral-spatial-wise attention (SSA-SiamNet) mechanism. The proposed SSA-SiamNet method can emphasize informative channels and locations and suppress less informative ones to refine the spectral-spatial features adaptively. Moreover, in the network training phase, the weighted contrastive loss function is used for more reliable separation of changed and unchanged pixels and to accelerate the convergence of the network. SSA-SiamNet was validated using four groups of bitemporal HSIs. The accuracy of CD using the SSA-SiamNet was found to be consistently greater than for ten benchmark methods

The hidden sterile neutrino and the (2+2) sum rule

We discuss oscillations of atmospheric and solar neutrinos into sterile neutrinos in the 2+2 scheme. A zeroth order sum rule requires equal probabilities for oscillation into nu_s and nu_tau in the solar+atmospheric data sample. Data does not favor this claim. Here we use scatter plots to assess corrections of the zeroth order sum rule when (i) the 4 x 4 neutrino mixing matrix assumes its full range of allowed values, and (ii) matter effects are included. We also introduce a related "product rule". We find that the sum rule is significantly relaxed, due to both the inclusion of the small mixing angles (which provide a short-baseline contribution) and to matter effects. The product rule is also dramatically altered. The observed relaxation of the sum rule weakens the case against the 2+2 model and the sterile neutrino. To invalidate the 2+2 model, a global fit to data with the small mixing angles included seems to be required.Comment: 43 pages, 11 figures (same as v2, accidental replacement

Generation of a humanized mouse model with both human immune system and liver cells to model hepatitis C virus infection and liver immunopathogenesis

Establishing a small animal model that accurately recapitulates hepatotropic pathogens, including hepatitis C virus (HCV) infection and immunopathogenesis, is essential for the study of hepatitis virus–induced liver disease and for therapeutics development. This protocol describes our recently developed humanized mouse model for studying HCV and other hepatotropic infections, human immune response and hepatitis and liver fibrosis. The first 5-h stage is the isolation of human liver progenitor and hematopoietic stem cells from fetal liver. Next, AFC8 immunodeficient mice are transplanted with the isolated progenitor/stem cells. This generally takes 2 h. The transplanted mice are then treated for a month with the mouse liver apoptosis–inducing AFC8 dimerizer and left for an additional 2-month period to permit human liver and immune cell growth as well as system reconstitution and development before inoculation with HCV clinical isolates. HCV infection, human immune response and liver disease are observed with high incidence from approximately 2 months after inoculation

Relic Neutrino Absorption Spectroscopy

Resonant annihilation of extremely high-energy cosmic neutrinos on big-bang relic anti-neutrinos (and vice versa) into Z-bosons leads to sizable absorption dips in the neutrino flux to be observed at Earth. The high-energy edges of these dips are fixed, via the resonance energies, by the neutrino masses alone. Their depths are determined by the cosmic neutrino background density, by the cosmological parameters determining the expansion rate of the universe, and by the large redshift history of the cosmic neutrino sources. We investigate the possibility of determining the existence of the cosmic neutrino background within the next decade from a measurement of these absorption dips in the neutrino flux. As a by-product, we study the prospects to infer the absolute neutrino mass scale. We find that, with the presently planned neutrino detectors (ANITA, Auger, EUSO, OWL, RICE, and SalSA) operating in the relevant energy regime above 10^{21} eV, relic neutrino absorption spectroscopy becomes a realistic possibility. It requires, however, the existence of extremely powerful neutrino sources, which should be opaque to nucleons and high-energy photons to evade present constraints. Furthermore, the neutrino mass spectrum must be quasi-degenerate to optimize the dip, which implies m_{nu} >~ 0.1 eV for the lightest neutrino. With a second generation of neutrino detectors, these demanding requirements can be relaxed considerably.Comment: 19 pages, 26 figures, REVTeX

A Humanized Mouse Model to Study Hepatitis C Virus Infection, Immune Response, and Liver Disease

Studies of hepatitis C virus (HCV) infection, immunopathogenesis, and resulting liver diseases have been hampered by the lack of a small animal model. We developed humanized mice with human immune system and liver tissues to improve the studies of hepatitis C pathogenesis and treatment

Distributed information consensus filters for simultaneous input and state estimation

This paper describes the distributed information filtering where a set of sensor networks are required to simultaneously estimate input and state of a linear discrete-time system from collaborative manner. Our research purpose is to develop a consensus strategy in which sensor nodes communicate within the network through a sequence of Kalman iterations and data diffusion. A novel recursive information filtering is proposed by integrating input estimation error into measurement data and weighted information matrices. On the fusing process, local system state filtering transmits estimation information using the consensus averaging algorithm, which penalizes the disagreement in a dynamic manner. A simulation example is provided to compare the performance of the distributed information filtering with optimal Gillijins–De Moor’s algorithm

Gate-tunable Topological Valley Transport in Bilayer Graphene

Valley pseudospin, the quantum degree of freedom characterizing the degenerate valleys in energy bands, is a distinct feature of two-dimensional Dirac materials. Similar to spin, the valley pseudospin is spanned by a time reversal pair of states, though the two valley pseudospin states transform to each other under spatial inversion. The breaking of inversion symmetry induces various valley-contrasted physical properties; for instance, valley-dependent topological transport is of both scientific and technological interests. Bilayer graphene (BLG) is a unique system whose intrinsic inversion symmetry can be controllably broken by a perpendicular electric field, offering a rare possibility for continuously tunable valley-topological transport. Here, we used a perpendicular gate electric field to break the inversion symmetry in BLG, and a giant nonlocal response was observed as a result of the topological transport of the valley pseudospin. We further showed that the valley transport is fully tunable by external gates, and that the nonlocal signal persists up to room temperature and over long distances. These observations challenge contemporary understanding of topological transport in a gapped system, and the robust topological transport may lead to future valleytronic applications

A proteogenomic analysis of Shigella flexneri using 2D LC-MALDI TOF/TOF

<p>Abstract</p> <p>Background</p> <p>New strategies for high-throughput sequencing are constantly appearing, leading to a great increase in the number of completely sequenced genomes. Unfortunately, computational genome annotation is out of step with this progress. Thus, the accurate annotation of these genomes has become a bottleneck of knowledge acquisition.</p> <p>Results</p> <p>We exploited a proteogenomic approach to improve conventional genome annotation by integrating proteomic data with genomic information. Using <it>Shigella flexneri </it>2a as a model, we identified total 823 proteins, including 187 hypothetical proteins. Among them, three annotated ORFs were extended upstream through comprehensive analysis against an in-house N-terminal extension database. Two genes, which could not be translated to their full length because of stop codon 'mutations' induced by genome sequencing errors, were revised and annotated as fully functional genes. Above all, seven new ORFs were discovered, which were not predicted in <it>S. flexneri </it>2a str.301 by any other annotation approaches. The transcripts of four novel ORFs were confirmed by RT-PCR assay. Additionally, most of these novel ORFs were overlapping genes, some even nested within the coding region of other known genes.</p> <p>Conclusions</p> <p>Our findings demonstrate that current <it>Shigella </it>genome annotation methods are not perfect and need to be improved. Apart from the validation of predicted genes at the protein level, the additional features of proteogenomic tools include revision of annotation errors and discovery of novel ORFs. The complementary dataset could provide more targets for those interested in <it>Shigella </it>to perform functional studies.</p

Anti- Japanese-Encephalitis-Viral Effects of Kaempferol and Daidzin and Their RNA-Binding Characteristics

Background: New therapeutic tools and molecular targets are needed for treatment of Japanese encephalitis virus (JEV) infections. JEV requires an a-1 translational frameshift to synthesize the NS1 ’ protein required for viral neuroinvasiveness. Several flavonoids have been shown to possess antiviral activity in vitro against a wide spectrum of viruses. To date, the antiviral activities of flavonol kaempferol (Kae) and isoflavonoid daidzin (Dai) against JEV have not been described. Methodology/Principal Findings: The 50 % cytotoxic concentration (CC50) and 50 % effective concentration (EC50) against JEV were investigated in BHK21 cells by MTS reduction. Activity against viral genomic RNA and proteins was measured by real-time RT-PCR and western blotting. The frameshift site RNA-binding characterization was also determined by electrospray ionization mass spectrometry, isothermal titration calorimetry and autodocking analysis. EC 50 values of Kae and Dai were 12.6 and 25.9 mM against JEV in cells pretreated before infection, whereas in cells infected before treatment, EC50 was 21.5 and 40.4 mM, respectively. Kae exhibited more potent activity against JEV and RNA binding in cells following internalization through direct inhibition of viral replication and protein expression, indicating that its antiviral activity was principally due to direct virucidal effects. The JEV frameshift site RNA (fsRNA) was selected as a target for assaying Kae and Dai. ITC of fsRNA revealed an apparent Kb value for Kae that was nine fold stronger than that for Dai. This binding was confirmed and localized to the RNA using ESI-MS and autodock analysis. Kae could form non-covalent complexes wit

Combining blue native polyacrylamide gel electrophoresis with liquid chromatography tandem mass spectrometry as an effective strategy for analyzing potential membrane protein complexes of Mycobacterium bovis bacillus Calmette-Guérin

<p>Abstract</p> <p>Background</p> <p>Tuberculosis is an infectious bacterial disease in humans caused primarily by <it>Mycobacterium tuberculosis</it>, and infects one-third of the world's total population. <it>Mycobacterium bovis </it>bacillus Calmette-Guérin (BCG) vaccine has been widely used to prevent tuberculosis worldwide since 1921. Membrane proteins play important roles in various cellular processes, and the protein-protein interactions involved in these processes may provide further information about molecular organization and cellular pathways. However, membrane proteins are notoriously under-represented by traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and little is known about mycobacterial membrane and membrane-associated protein complexes. Here we investigated <it>M. bovis </it>BCG by an alternative proteomic strategy coupling blue native PAGE to liquid chromatography tandem mass spectrometry (LC-MS/MS) to characterize potential protein-protein interactions in membrane fractions.</p> <p>Results</p> <p>Using this approach, we analyzed native molecular composition of protein complexes in BCG membrane fractions. As a result, 40 proteins (including 12 integral membrane proteins), which were organized in 9 different gel bands, were unambiguous identified. The proteins identified have been experimentally confirmed using 2-D SDS PAGE. We identified MmpL8 and four neighboring proteins that were involved in lipid transport complexes, and all subunits of ATP synthase complex in their monomeric states. Two phenolpthiocerol synthases and three arabinosyltransferases belonging to individual operons were obtained in different gel bands. Furthermore, two giant multifunctional enzymes, Pks7 and Pks8, and four mycobacterial Hsp family members were determined. Additionally, seven ribosomal proteins involved in polyribosome complex and two subunits of the succinate dehydrogenase complex were also found. Notablely, some proteins with high hydrophobicity or multiple transmembrane helixes were identified well in our work.</p> <p>Conclusions</p> <p>In this study, we utilized LC-MS/MS in combination with blue native PAGE to characterize modular components of multiprotein complexes in BCG membrane fractions. The results demonstrated that the proteomic strategy was a reliable and reproducible tool for analysis of BCG multiprotein complexes. The identification in our study may provide some evidence for further study of BCG protein interaction.</p