The nonstructural protein 8 (nsp8) of the SARS coronavirus interacts with its ORF6 accessory protein

International Nuclear Information System (INIS)

Kumar, Purnima; Gunalan, Vithiagaran; Liu Boping; Chow, Vincent T.K.; Druce, Julian; Birch, Chris; Catton, Mike; Fielding, Burtram C.; Tan, Yee-Joo; Lal, Sunil K.

2007-01-01

Severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) caused a severe outbreak in several regions of the world in 2003. The SARS-CoV genome is predicted to contain 14 functional open reading frames (ORFs). The first ORF (1a and 1b) encodes a large polyprotein that is cleaved into nonstructural proteins (nsp). The other ORFs encode for four structural proteins (spike, membrane, nucleocapsid and envelope) as well as eight SARS-CoV-specific accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b and 9b). In this report we have cloned the predicted nsp8 gene and the ORF6 gene of the SARS-CoV and studied their abilities to interact with each other. We expressed the two proteins as fusion proteins in the yeast two-hybrid system to demonstrate protein-protein interactions and tested the same using a yeast genetic cross. Further the strength of the interaction was measured by challenging growth of the positive interaction clones on increasing gradients of 2-amino trizole. The interaction was then verified by expressing both proteins separately in-vitro in a coupled-transcription translation system and by coimmunoprecipitation in mammalian cells. Finally, colocalization experiments were performed in SARS-CoV infected Vero E6 mammalian cells to confirm the nsp8-ORF6 interaction. To the best of our knowledge, this is the first report of the interaction between a SARS-CoV accessory protein and nsp8 and our findings suggest that ORF6 protein may play a role in virus replication

Joint Probability-Based Neuronal Spike Train Classification

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Yan Chen

2009-01-01

Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

A virus-binding hot spot on human angiotensin-converting enzyme 2 is critical for binding of two different coronaviruses.

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Wu, Kailang; Chen, Lang; Peng, Guiqing; Zhou, Wenbo; Pennell, Christopher A; Mansky, Louis M; Geraghty, Robert J; Li, Fang

2011-06-01

How viruses evolve to select their receptor proteins for host cell entry is puzzling. We recently determined the crystal structures of NL63 coronavirus (NL63-CoV) and SARS coronavirus (SARS-CoV) receptor-binding domains (RBDs), each complexed with their common receptor, human angiotensin-converting enzyme 2 (hACE2), and proposed the existence of a virus-binding hot spot on hACE2. Here we investigated the function of this hypothetical hot spot using structure-guided biochemical and functional assays. The hot spot consists of a salt bridge surrounded by hydrophobic tunnel walls. Mutations that disturb the hot spot structure have significant effects on virus/receptor interactions, revealing critical energy contributions from the hot spot structure. The tunnel structure at the NL63-CoV/hACE2 interface is more compact than that at the SARS-CoV/hACE2 interface, and hence RBD/hACE2 binding affinities are decreased either by NL63-CoV mutations decreasing the tunnel space or by SARS-CoV mutations increasing the tunnel space. Furthermore, NL63-CoV RBD inhibits hACE2-dependent transduction by SARS-CoV spike protein, a successful application of the hot spot theory that has the potential to become a new antiviral strategy against SARS-CoV infections. These results suggest that the structural features of the hot spot on hACE2 were among the driving forces for the convergent evolution of NL63-CoV and SARS-CoV.

Palmitoylation of SARS-CoV S protein is necessary for partitioning into detergent-resistant membranes and cell-cell fusion but not interaction with M protein

International Nuclear Information System (INIS)

McBride, Corrin E.; Machamer, Carolyn E.

2010-01-01

Coronaviruses are enveloped RNA viruses that generally cause mild disease in humans. However, the recently emerged coronavirus that caused severe acute respiratory syndrome (SARS-CoV) is the most pathogenic human coronavirus discovered to date. The SARS-CoV spike (S) protein mediates virus entry by binding cellular receptors and inducing fusion between the viral envelope and the host cell membrane. Coronavirus S proteins are palmitoylated, which may affect function. Here, we created a non-palmitoylated SARS-CoV S protein by mutating all nine cytoplasmic cysteine residues. Palmitoylation of SARS-CoV S was required for partitioning into detergent-resistant membranes and for cell-cell fusion. Surprisingly, however, palmitoylation of S was not required for interaction with SARS-CoV M protein. This contrasts with the requirement for palmitoylation of mouse hepatitis virus S protein for interaction with M protein and may point to important differences in assembly and infectivity of these two coronaviruses.

Crystal structure of NL63 respiratory coronavirus receptor-binding domain complexed with its human receptor

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Wu, Kailang; Li, Weikai; Peng, Guiqing; Li, Fang; (Harvard-Med); (UMM-MED)

2010-03-04

NL63 coronavirus (NL63-CoV), a prevalent human respiratory virus, is the only group I coronavirus known to use angiotensin-converting enzyme 2 (ACE2) as its receptor. Incidentally, ACE2 is also used by group II SARS coronavirus (SARS-CoV). We investigated how different groups of coronaviruses recognize the same receptor, whereas homologous group I coronaviruses recognize different receptors. We determined the crystal structure of NL63-CoV spike protein receptor-binding domain (RBD) complexed with human ACE2. NL63-CoV RBD has a novel {beta}-sandwich core structure consisting of 2 layers of {beta}-sheets, presenting 3 discontinuous receptor-binding motifs (RBMs) to bind ACE2. NL63-CoV and SARS-CoV have no structural homology in RBD cores or RBMs; yet the 2 viruses recognize common ACE2 regions, largely because of a 'virus-binding hotspot' on ACE2. Among group I coronaviruses, RBD cores are conserved but RBMs are variable, explaining how these viruses recognize different receptors. These results provide a structural basis for understanding viral evolution and virus-receptor interactions.

Ezrin interacts with the SARS coronavirus Spike protein and restrains infection at the entry stage.

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Jean Kaoru Millet

Full Text Available BACKGROUND: Entry of Severe Acute Respiratory Syndrome coronavirus (SARS-CoV and its envelope fusion with host cell membrane are controlled by a series of complex molecular mechanisms, largely dependent on the viral envelope glycoprotein Spike (S. There are still many unknowns on the implication of cellular factors that regulate the entry process. METHODOLOGY/PRINCIPAL FINDINGS: We performed a yeast two-hybrid screen using as bait the carboxy-terminal endodomain of S, which faces the cytosol during and after opening of the fusion pore at early stages of the virus life cycle. Here we show that the ezrin membrane-actin linker interacts with S endodomain through the F1 lobe of its FERM domain and that both the eight carboxy-terminal amino-acids and a membrane-proximal cysteine cluster of S endodomain are important for this interaction in vitro. Interestingly, we found that ezrin is present at the site of entry of S-pseudotyped lentiviral particles in Vero E6 cells. Targeting ezrin function by small interfering RNA increased S-mediated entry of pseudotyped particles in epithelial cells. Furthermore, deletion of the eight carboxy-terminal amino acids of S enhanced S-pseudotyped particles infection. Expression of the ezrin dominant negative FERM domain enhanced cell susceptibility to infection by SARS-CoV and S-pseudotyped particles and potentiated S-dependent membrane fusion. CONCLUSIONS/SIGNIFICANCE: Ezrin interacts with SARS-CoV S endodomain and limits virus entry and fusion. Our data present a novel mechanism involving a cellular factor in the regulation of S-dependent early events of infection.

SARS-coronavirus spike S2 domain flanked by cysteine residues C822 and C833 is important for activation of membrane fusion

International Nuclear Information System (INIS)

Madu, Ikenna G.; Belouzard, Sandrine; Whittaker, Gary R.

2009-01-01

The S2 domain of the coronavirus spike (S) protein is known to be responsible for mediating membrane fusion. In addition to a well-recognized cleavage site at the S1-S2 boundary, a second proteolytic cleavage site has been identified in the severe acute respiratory syndrome coronavirus (SARS-CoV) S2 domain (R797). C-terminal to this S2 cleavage site is a conserved region flanked by cysteine residues C822 and C833. Here, we investigated the importance of this well conserved region for SARS-CoV S-mediated fusion activation. We show that the residues between C822-C833 are well conserved across all coronaviruses. Mutagenic analysis of SARS-CoV S, combined with cell-cell fusion and pseudotyped virion infectivity assays, showed a critical role for the core-conserved residues C822, D830, L831, and C833. Based on available predictive models, we propose that the conserved domain flanked by cysteines 822 and 833 forms a loop structure that interacts with components of the SARS-CoV S trimer to control the activation of membrane fusion.

SARS – Koch´Postulates proved.

Indian Academy of Sciences (India)

SARS – Koch´Postulates proved. Novel coronavirus identified from fluids of patients. Virus cultured in Vero cell line. Sera of patients have antibodies to virus. Cultured virus produces disease in Macaque monkeys. -produces specific immune response; -isolated virus is SARS CoV; -pathology similar to human.

Dictionary-Based Stochastic Expectation–Maximization for SAR Amplitude Probability Density Function Estimation

OpenAIRE

Moser , Gabriele; Zerubia , Josiane; Serpico , Sebastiano B.

2006-01-01

International audience; In remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of the pixel intensities. This paper deals with the problem of probability density function (pdf) estimation in the context of synthetic aperture radar (SAR) amplitude data analysis. Several theoretical and heuristic models for the pdfs of SAR data have been proposed in the literature, which have been proved to be effective for different land-cov...

Dendritic cell targeted chitosan nanoparticles for nasal DNA immunization against SARS CoV nucleocapsid protein.

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Raghuwanshi, Dharmendra; Mishra, Vivek; Das, Dipankar; Kaur, Kamaljit; Suresh, Mavanur R

2012-04-02

This work investigates the formulation and in vivo efficacy of dendritic cell (DC) targeted plasmid DNA loaded biotinylated chitosan nanoparticles for nasal immunization against nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) as antigen. The induction of antigen-specific mucosal and systemic immune response at the site of virus entry is a major challenge for vaccine design. Here, we designed a strategy for noninvasive receptor mediated gene delivery to nasal resident DCs. The pDNA loaded biotinylated chitosan nanoparticles were prepared using a complex coacervation process and characterized for size, shape, surface charge, plasmid DNA loading and protection against nuclease digestion. The pDNA loaded biotinylated chitosan nanoparticles were targeted with bifunctional fusion protein (bfFp) vector for achieving DC selective targeting. The bfFp is a recombinant fusion protein consisting of truncated core-streptavidin fused with anti-DEC-205 single chain antibody (scFv). The core-streptavidin arm of fusion protein binds with biotinylated nanoparticles, while anti-DEC-205 scFv imparts targeting specificity to DC DEC-205 receptor. We demonstrate that intranasal administration of bfFp targeted formulations along with anti-CD40 DC maturation stimuli enhanced magnitude of mucosal IgA as well as systemic IgG against N protein. The strategy led to the detection of augmented levels of N protein specific systemic IgG and nasal IgA antibodies. However, following intranasal delivery of naked pDNA no mucosal and systemic immune responses were detected. A parallel comparison of targeted formulations using intramuscular and intranasal routes showed that the intramuscular route is superior for induction of systemic IgG responses compared with the intranasal route. Our results suggest that targeted pDNA delivery through a noninvasive intranasal route can be a strategy for designing low-dose vaccines.

Differential sensitivity of bat cells to infection by enveloped RNA viruses: coronaviruses, paramyxoviruses, filoviruses, and influenza viruses.

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Markus Hoffmann

Full Text Available Bats (Chiroptera host major human pathogenic viruses including corona-, paramyxo, rhabdo- and filoviruses. We analyzed six different cell lines from either Yinpterochiroptera (including African flying foxes and a rhinolophid bat or Yangochiroptera (genera Carollia and Tadarida for susceptibility to infection by different enveloped RNA viruses. None of the cells were sensitive to infection by transmissible gastroenteritis virus (TGEV, a porcine coronavirus, or to infection mediated by the Spike (S protein of SARS-coronavirus (SARS-CoV incorporated into pseudotypes based on vesicular stomatitis virus (VSV. The resistance to infection was overcome if cells were transfected to express the respective cellular receptor, porcine aminopeptidase N for TGEV or angiotensin-converting enzyme 2 for SARS-CoV. VSV pseudotypes containing the S proteins of two bat SARS-related CoV (Bg08 and Rp3 were unable to infect any of the six tested bat cell lines. By contrast, viral pseudotypes containing the surface protein GP of Marburg virus from the family Filoviridae infected all six cell lines though at different efficiency. Notably, all cells were sensitive to infection by two paramyxoviruses (Sendai virus and bovine respiratory syncytial virus and three influenza viruses from different subtypes. These results indicate that bat cells are more resistant to infection by coronaviruses than to infection by paramyxoviruses, filoviruses and influenza viruses. Furthermore, these results show a receptor-dependent restriction of the infection of bat cells by CoV. The implications for the isolation of coronaviruses from bats are discussed.

Selection of SARS-Coronavirus-specific B cell epitopes by phage peptide library screening and evaluation of the immunological effect of epitope-based peptides on mice

International Nuclear Information System (INIS)

Yu Hua; Jiang Lifang; Fang Danyun; Yan Huijun; Zhou Jingjiao; Zhou Junmei; Liang Yu; Gao Yang; Zhao, Wei; Long Beiguo

2007-01-01

Antibodies to SARS-Coronavirus (SARS-CoV)-specific B cell epitopes might recognize the pathogen and interrupt its adherence to and penetration of host cells. Hence, these epitopes could be useful for diagnosis and as vaccine constituents. Using the phage-displayed peptide library screening method and purified Fab fragments of immunoglobulin G (IgG Fab) from normal human sera and convalescent sera from SARS-CoV-infected patients as targets, 11 B cell epitopes of SARS-CoV spike glycoprotein (S protein) and membrane protein (M protein) were screened. After a bioinformatics tool was used to analyze these epitopes, four epitope-based S protein dodecapeptides corresponding to the predominant epitopes were chosen for synthesis. Their antigenic specificities and immunogenicities were studied in vitro and in vivo. Flow cytometry and ELISPOT analysis of lymphocytes as well as a serologic analysis of antibody showed that these peptides could trigger a rapid, highly effective, and relatively safe immune response in BALB/c mice. These findings might aid development of SARS diagnostics and vaccines. Moreover, the role of S and M proteins as important surface antigens is confirmed

Evidence supporting a zoonotic origin of human coronavirus strain NL63.

Science.gov (United States)

Huynh, Jeremy; Li, Shimena; Yount, Boyd; Smith, Alexander; Sturges, Leslie; Olsen, John C; Nagel, Juliet; Johnson, Joshua B; Agnihothram, Sudhakar; Gates, J Edward; Frieman, Matthew B; Baric, Ralph S; Donaldson, Eric F

2012-12-01

The relationship between bats and coronaviruses (CoVs) has received considerable attention since the severe acute respiratory syndrome (SARS)-like CoV was identified in the Chinese horseshoe bat (Rhinolophidae) in 2005. Since then, several bats throughout the world have been shown to shed CoV sequences, and presumably CoVs, in the feces; however, no bat CoVs have been isolated from nature. Moreover, there are very few bat cell lines or reagents available for investigating CoV replication in bat cells or for isolating bat CoVs adapted to specific bat species. Here, we show by molecular clock analysis that alphacoronavirus (α-CoV) sequences derived from the North American tricolored bat (Perimyotis subflavus) are predicted to share common ancestry with human CoV (HCoV)-NL63, with the most recent common ancestor between these viruses occurring approximately 563 to 822 years ago. Further, we developed immortalized bat cell lines from the lungs of this bat species to determine if these cells were capable of supporting infection with HCoVs. While SARS-CoV, mouse-adapted SARS-CoV (MA15), and chimeric SARS-CoVs bearing the spike genes of early human strains replicated inefficiently, HCoV-NL63 replicated for multiple passages in the immortalized lung cells from this bat species. These observations support the hypothesis that human CoVs are capable of establishing zoonotic-reverse zoonotic transmission cycles that may allow some CoVs to readily circulate and exchange genetic material between strains found in bats and other mammals, including humans.

Feline coronavirus: Insights into viral pathogenesis based on the spike protein structure and function.

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Jaimes, Javier A; Whittaker, Gary R

2018-04-01

Feline coronavirus (FCoV) is an etiological agent that causes a benign enteric illness and the fatal systemic disease feline infectious peritonitis (FIP). The FCoV spike (S) protein is considered the viral regulator for binding and entry to the cell. This protein is also involved in FCoV tropism and virulence, as well as in the switch from enteric disease to FIP. This regulation is carried out by spike's major functions: receptor binding and virus-cell membrane fusion. In this review, we address important aspects in FCoV genetics, replication and pathogenesis, focusing on the role of S. To better understand this, FCoV S protein models were constructed, based on the human coronavirus NL63 (HCoV-NL63) S structure. We describe the specific structural characteristics of the FCoV S, in comparison with other coronavirus spikes. We also revise the biochemical events needed for FCoV S activation and its relation to the structural features of the protein. Copyright © 2018 Elsevier Inc. All rights reserved.

Vaccine efficacy in senescent mice challenged with recombinant SARS-CoV bearing epidemic and zoonotic spike variants.

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Damon Deming

2006-12-01

Full Text Available In 2003, severe acute respiratory syndrome coronavirus (SARS-CoV was identified as the etiological agent of severe acute respiratory syndrome, a disease characterized by severe pneumonia that sometimes results in death. SARS-CoV is a zoonotic virus that crossed the species barrier, most likely originating from bats or from other species including civets, raccoon dogs, domestic cats, swine, and rodents. A SARS-CoV vaccine should confer long-term protection, especially in vulnerable senescent populations, against both the 2003 epidemic strains and zoonotic strains that may yet emerge from animal reservoirs. We report the comprehensive investigation of SARS vaccine efficacy in young and senescent mice following homologous and heterologous challenge.Using Venezuelan equine encephalitis virus replicon particles (VRP expressing the 2003 epidemic Urbani SARS-CoV strain spike (S glycoprotein (VRP-S or the nucleocapsid (N protein from the same strain (VRP-N, we demonstrate that VRP-S, but not VRP-N vaccines provide complete short- and long-term protection against homologous strain challenge in young and senescent mice. To test VRP vaccine efficacy against a heterologous SARS-CoV, we used phylogenetic analyses, synthetic biology, and reverse genetics to construct a chimeric virus (icGDO3-S encoding a synthetic S glycoprotein gene of the most genetically divergent human strain, GDO3, which clusters among the zoonotic SARS-CoV. icGD03-S replicated efficiently in human airway epithelial cells and in the lungs of young and senescent mice, and was highly resistant to neutralization with antisera directed against the Urbani strain. Although VRP-S vaccines provided complete short-term protection against heterologous icGD03-S challenge in young mice, only limited protection was seen in vaccinated senescent animals. VRP-N vaccines not only failed to protect from homologous or heterologous challenge, but resulted in enhanced immunopathology with eosinophilic

Palmitoylation of the cysteine-rich endodomain of the SARS-coronavirus spike glycoprotein is important for spike-mediated cell fusion

International Nuclear Information System (INIS)

Petit, Chad M.; Chouljenko, Vladimir N.; Iyer, Arun; Colgrove, Robin; Farzan, Michael; Knipe, David M.; Kousoulas, K.G.

2007-01-01

The SARS-coronavirus (SARS-CoV) is the etiological agent of the severe acute respiratory syndrome (SARS). The SARS-CoV spike (S) glycoprotein mediates membrane fusion events during virus entry and virus-induced cell-to-cell fusion. The cytoplasmic portion of the S glycoprotein contains four cysteine-rich amino acid clusters. Individual cysteine clusters were altered via cysteine-to-alanine amino acid replacement and the modified S glycoproteins were tested for their transport to cell-surfaces and ability to cause cell fusion in transient transfection assays. Mutagenesis of the cysteine cluster I, located immediately proximal to the predicted transmembrane, domain did not appreciably reduce cell-surface expression, although S-mediated cell fusion was reduced by more than 50% in comparison to the wild-type S. Similarly, mutagenesis of the cysteine cluster II located adjacent to cluster I reduced S-mediated cell fusion by more than 60% compared to the wild-type S, while cell-surface expression was reduced by less than 20%. Mutagenesis of cysteine clusters III and IV did not appreciably affect S cell-surface expression or S-mediated cell fusion. The wild-type S was palmitoylated as evidenced by the efficient incorporation of 3 H-palmitic acid in wild-type S molecules. S glycoprotein palmitoylation was significantly reduced for mutant glycoproteins having cluster I and II cysteine changes, but was largely unaffected for cysteine cluster III and IV mutants. These results show that the S cytoplasmic domain is palmitoylated and that palmitoylation of the membrane proximal cysteine clusters I and II may be important for S-mediated cell fusion

The nucleocapsid proteins of mouse hepatitis virus and severe acute respiratory syndrome coronavirus share the same IFN-β antagonizing mechanism: attenuation of PACT-mediated RIG-I/ MDA5 activation.

Science.gov (United States)

Ding, Zhen; Fang, Liurong; Yuan, Shuangling; Zhao, Ling; Wang, Xunlei; Long, Siwen; Wang, Mohan; Wang, Dang; Foda, Mohamed Frahat; Xiao, Shaobo

2017-07-25

Coronaviruses (CoVs) are a huge threat to both humans and animals and have evolved elaborate mechanisms to antagonize interferons (IFNs). Nucleocapsid (N) protein is the most abundant viral protein in CoV-infected cells, and has been identified as an innate immunity antagonist in several CoVs, including mouse hepatitis virus (MHV) and severe acute respiratory syndrome (SARS)-CoV. However, the underlying molecular mechanism(s) remain unclear. In this study, we found that MHV N protein inhibited Sendai virus and poly(I:C)-induced IFN-β production by targeting a molecule upstream of retinoic acid-induced gene I (RIG-I) and melanoma differentiation gene 5 (MDA5). Further studies showed that both MHV and SARS-CoV N proteins directly interacted with protein activator of protein kinase R (PACT), a cellular dsRNA-binding protein that can bind to RIG-I and MDA5 to activate IFN production. The N-PACT interaction sequestered the association of PACT and RIG-I/MDA5, which in turn inhibited IFN-β production. However, the N proteins from porcine epidemic diarrhea virus (PEDV) and porcine reproductive and respiratory syndrome virus (PRRSV), which are also classified in the order Nidovirales, did not interact and counteract with PACT. Taken together, our present study confirms that both MHV and SARS-CoV N proteins can perturb the function of cellular PACT to circumvent the innate antiviral response. However, this strategy does not appear to be used by all CoVs N proteins.

Identification of two critical amino acid residues of the severe acute respiratory syndrome coronavirus spike protein for its variation in zoonotic tropism transition via a double substitution strategy.

Science.gov (United States)

Qu, Xiu-Xia; Hao, Pei; Song, Xi-Jun; Jiang, Si-Ming; Liu, Yan-Xia; Wang, Pei-Gang; Rao, Xi; Song, Huai-Dong; Wang, Sheng-Yue; Zuo, Yu; Zheng, Ai-Hua; Luo, Min; Wang, Hua-Lin; Deng, Fei; Wang, Han-Zhong; Hu, Zhi-Hong; Ding, Ming-Xiao; Zhao, Guo-Ping; Deng, Hong-Kui

2005-08-19

Severe acute respiratory syndrome coronavirus (SARS-CoV) is a recently identified human coronavirus. The extremely high homology of the viral genomic sequences between the viruses isolated from human (huSARS-CoV) and those of palm civet origin (pcSARS-CoV) suggested possible palm civet-to-human transmission. Genetic analysis revealed that the spike (S) protein of pcSARS-CoV and huSARS-CoV was subjected to the strongest positive selection pressure during transmission, and there were six amino acid residues within the receptor-binding domain of the S protein being potentially important for SARS progression and tropism. Using the single-round infection assay, we found that a two-amino acid substitution (N479K/T487S) of a huSARS-CoV for those of pcSARS-CoV almost abolished its infection of human cells expressing the SARS-CoV receptor ACE2 but no effect upon the infection of mouse ACE2 cells. Although single substitution of these two residues had no effects on the infectivity of huSARS-CoV, these recombinant S proteins bound to human ACE2 with different levels of reduced affinity, and the two-amino acid-substituted S protein showed extremely low affinity. On the contrary, substitution of these two amino acid residues of pcSARS-CoV for those of huSRAS-CoV made pcSARS-CoV capable of infecting human ACE2-expressing cells. These results suggest that amino acid residues at position 479 and 487 of the S protein are important determinants for SARS-CoV tropism and animal-to-human transmission.

Cloaked similarity between HIV-1 and SARS-CoV suggests an anti-SARS strategy

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Kliger Yossef

2003-09-01

Full Text Available Abstract Background Severe acute respiratory syndrome (SARS is a febrile respiratory illness. The disease has been etiologically linked to a novel coronavirus that has been named the SARS-associated coronavirus (SARS-CoV, whose genome was recently sequenced. Since it is a member of the Coronaviridae, its spike protein (S2 is believed to play a central role in viral entry by facilitating fusion between the viral and host cell membranes. The protein responsible for viral-induced membrane fusion of HIV-1 (gp41 differs in length, and has no sequence homology with S2. Results Sequence analysis reveals that the two viral proteins share the sequence motifs that construct their active conformation. These include (1 an N-terminal leucine/isoleucine zipper-like sequence, and (2 a C-terminal heptad repeat located upstream of (3 an aromatic residue-rich region juxtaposed to the (4 transmembrane segment. Conclusions This study points to a similar mode of action for the two viral proteins, suggesting that anti-viral strategy that targets the viral-induced membrane fusion step can be adopted from HIV-1 to SARS-CoV. Recently the FDA approved Enfuvirtide, a synthetic peptide corresponding to the C-terminal heptad repeat of HIV-1 gp41, as an anti-AIDS agent. Enfuvirtide and C34, another anti HIV-1 peptide, exert their inhibitory activity by binding to a leucine/isoleucine zipper-like sequence in gp41, thus inhibiting a conformational change of gp41 required for its activation. We suggest that peptides corresponding to the C-terminal heptad repeat of the S2 protein may serve as inhibitors for SARS-CoV entry.

Severe acute respiratory syndrome vaccine efficacy in ferrets: whole killed virus and adenovirus-vectored vaccines.

Science.gov (United States)

See, Raymond H; Petric, Martin; Lawrence, David J; Mok, Catherine P Y; Rowe, Thomas; Zitzow, Lois A; Karunakaran, Karuna P; Voss, Thomas G; Brunham, Robert C; Gauldie, Jack; Finlay, B Brett; Roper, Rachel L

2008-09-01

Although the 2003 severe acute respiratory syndrome (SARS) outbreak was controlled, repeated transmission of SARS coronavirus (CoV) over several years makes the development of a SARS vaccine desirable. We performed a comparative evaluation of two SARS vaccines for their ability to protect against live SARS-CoV intranasal challenge in ferrets. Both the whole killed SARS-CoV vaccine (with and without alum) and adenovirus-based vectors encoding the nucleocapsid (N) and spike (S) protein induced neutralizing antibody responses and reduced viral replication and shedding in the upper respiratory tract and progression of virus to the lower respiratory tract. The vaccines also diminished haemorrhage in the thymus and reduced the severity and extent of pneumonia and damage to lung epithelium. However, despite high neutralizing antibody titres, protection was incomplete for all vaccine preparations and administration routes. Our data suggest that a combination of vaccine strategies may be required for effective protection from this pathogen. The ferret may be a good model for SARS-CoV infection because it is the only model that replicates the fever seen in human patients, as well as replicating other SARS disease features including infection by the respiratory route, clinical signs, viral replication in upper and lower respiratory tract and lung damage.

CovR Regulates Streptococcus mutans Susceptibility To Complement Immunity and Survival in Blood

Science.gov (United States)

Alves, Lívia A.; Nomura, Ryota; Mariano, Flávia S.; Harth-Chu, Erika N.; Stipp, Rafael N.; Nakano, Kazuhiko

2016-01-01

Streptococcus mutans, a major pathogen of dental caries, may promote systemic infections after accessing the bloodstream from oral niches. In this study, we investigate pathways of complement immunity against S. mutans and show that the orphan regulator CovR (CovRSm) modulates susceptibility to complement opsonization and survival in blood. S. mutans blood isolates showed reduced susceptibility to C3b deposition compared to oral isolates. Reduced expression of covRSm in blood strains was associated with increased transcription of CovRSm-repressed genes required for S. mutans interactions with glucans (gbpC, gbpB, and epsC), sucrose-derived exopolysaccharides (EPS). Consistently, blood strains showed an increased capacity to bind glucan in vitro. Deletion of covRSm in strain UA159 (UAcov) impaired C3b deposition and binding to serum IgG and C-reactive protein (CRP) as well as phagocytosis through C3b/iC3b receptors and killing by neutrophils. Opposite effects were observed in mutants of gbpC, epsC, or gtfBCD (required for glucan synthesis). C3b deposition on UA159 was abolished in C1q-depleted serum, implying that the classical pathway is essential for complement activation on S. mutans. Growth in sucrose-containing medium impaired the binding of C3b and IgG to UA159, UAcov, and blood isolates but had absent or reduced effects on C3b deposition in gtfBCD, gbpC, and epsC mutants. UAcov further showed increased ex vivo survival in human blood in an EPS-dependent way. Consistently, reduced survival was observed for the gbpC and epsC mutants. Finally, UAcov showed an increased ability to cause bacteremia in a rat model. These results reveal that CovRSm modulates systemic virulence by regulating functions affecting S. mutans susceptibility to complement opsonization. PMID:27572331

Middle East Respiratory Syndrome Coronavirus Nonstructural Protein 16 Is Necessary for Interferon Resistance and Viral Pathogenesis

Energy Technology Data Exchange (ETDEWEB)

Menachery, Vineet D.; Gralinski, Lisa E.; Mitchell, Hugh D.; Dinnon, Kenneth H.; Leist, Sarah R.; Yount, Boyd L.; Graham, Rachel L.; McAnarney, Eileen T.; Stratton, Kelly G.; Cockrell, Adam S.; Debbink, Kari; Sims, Amy C.; Waters, Katrina M.; Baric, Ralph S.; Fernandez-Sesma, Ana

2017-11-15

Coronaviruses (CoVs) encode a mixture of highly conserved and novel genes, as well as genetic elements necessary for infection and pathogenesis, raising the possibility of common targets for attenuation and therapeutic design. In this study, we focused on highly conserved nonstructural protein 16 (NSP16), a viral 2'O-methyltransferase (2'O-MTase) that encodes critical functions in immune modulation and infection. Using reverse genetics, we disrupted a key motif in the conserved KDKE motif of Middle East respiratory syndrome CoV (MERS-CoV) NSP16 (D130A) and evaluated the effect on viral infection and pathogenesis. While the absence of 2'O-MTase activity had only a marginal impact on propagation and replication in Vero cells, dNSP16 mutant MERS-CoV demonstrated significant attenuation relative to the control both in primary human airway cell cultures andin vivo. Further examination indicated that dNSP16 mutant MERS-CoV had a type I interferon (IFN)-based attenuation and was partially restored in the absence of molecules of IFN-induced proteins with tetratricopeptide repeats. Importantly, the robust attenuation permitted the use of dNSP16 mutant MERS-CoV as a live attenuated vaccine platform protecting from a challenge with a mouse-adapted MERS-CoV strain. These studies demonstrate the importance of the conserved 2'O-MTase activity for CoV pathogenesis and highlight NSP16 as a conserved universal target for rapid live attenuated vaccine design in an expanding CoV outbreak setting.

IMPORTANCECoronavirus (CoV) emergence in both humans and livestock represents a significant threat to global public health, as evidenced by the sudden emergence of severe acute respiratory syndrome CoV (SARS-CoV), MERS-CoV, porcine epidemic diarrhea virus, and swine delta CoV in the 21st century. These studies describe an approach that

The coronavirus spike protein : mechanisms of membrane fusion and virion incorporation

NARCIS (Netherlands)

Bosch, B.J.

2004-01-01

The coronavirus spike protein is a membrane-anchored glycoprotein responsible for virus-cell attachment and membrane fusion, prerequisites for a successful virus infection. In this thesis, two aspects are described regarding the molecular biology of the coronavirus spike protein: its membrane fusion

Human Coronavirus HKU1 Spike Protein Uses O-Acetylated Sialic Acid as an Attachment Receptor Determinant and Employs Hemagglutinin-Esterase Protein as a Receptor-Destroying Enzyme.

Science.gov (United States)

Huang, Xingchuan; Dong, Wenjuan; Milewska, Aleksandra; Golda, Anna; Qi, Yonghe; Zhu, Quan K; Marasco, Wayne A; Baric, Ralph S; Sims, Amy C; Pyrc, Krzysztof; Li, Wenhui; Sui, Jianhua

2015-07-01

Human coronavirus (hCoV) HKU1 is one of six hCoVs identified to date and the only one with an unidentified cellular receptor. hCoV-HKU1 encodes a hemagglutinin-esterase (HE) protein that is unique to the group a betacoronaviruses (group 2a). The function of HKU1-HE remains largely undetermined. In this study, we examined binding of the S1 domain of hCoV-HKU1 spike to a panel of cells and found that the S1 could specifically bind on the cell surface of a human rhabdomyosarcoma cell line, RD. Pretreatment of RD cells with neuraminidase (NA) and trypsin greatly reduced the binding, suggesting that the binding was mediated by sialic acids on glycoproteins. However, unlike other group 2a CoVs, e.g., hCoV-OC43, for which 9-O-acetylated sialic acid (9-O-Ac-Sia) serves as a receptor determinant, HKU1-S1 bound with neither 9-O-Ac-Sia-containing glycoprotein(s) nor rat and mouse erythrocytes. Nonetheless, the HKU1-HE was similar to OC43-HE, also possessed sialate-O-acetylesterase activity, and acted as a receptor-destroying enzyme (RDE) capable of eliminating the binding of HKU1-S1 to RD cells, whereas the O-acetylesterase-inactive HKU1-HE mutant lost this capacity. Using primary human ciliated airway epithelial (HAE) cell cultures, the only in vitro replication model for hCoV-HKU1 infection, we confirmed that pretreatment of HAE cells with HE but not the enzymatically inactive mutant blocked hCoV-HKU1 infection. These results demonstrate that hCoV-HKU1 exploits O-Ac-Sia as a cellular attachment receptor determinant to initiate the infection of host cells and that its HE protein possesses the corresponding sialate-O-acetylesterase RDE activity. Human coronaviruses (hCoV) are important human respiratory pathogens. Among the six hCoVs identified to date, only hCoV-HKU1 has no defined cellular receptor. It is also unclear whether hemagglutinin-esterase (HE) protein plays a role in viral entry. In this study, we found that, similarly to other members of the group 2a CoVs, sialic

Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

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Ji'an Pan

Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

Pains and Gains from China's Experiences with Emerging Epidemics: From SARS to H7N9

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Wei, Pengfei; Cai, Zelang; Hua, Jinwen; Yu, Weijia; Chen, Jiajie; Kang, Kang; Qiu, Congling; Ye, Lanlan; Hu, Jiayun; Ji, Kunmei

2016-01-01

Over the recent decades, China experienced several emerging virus outbreaks including those caused by the severe acute respiratory syndrome- (SARS-) coronavirus (Cov), H5N1 virus, and H7N9 virus. The SARS tragedy revealed faults in China’s infectious disease prevention system, propelling the Chinese government to enact reforms that enabled better combating of the subsequent H1N1 and H7N9 avian flu epidemics. The system is buttressed by three fundamental, mutually reinforcing components: (1) e...

Generation of human antibody fragments recognizing distinct epitopes of the nucleocapsid (N SARS-CoV protein using a phage display approach

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Grasso Felicia

2005-09-01

Full Text Available Abstract Background Severe acute respiratory syndrome (SARS-CoV is a newly emerging virus that causes SARS with high mortality rate in infected people. Successful control of the global SARS epidemic will require rapid and sensitive diagnostic tests to monitor its spread, as well as, the development of vaccines and new antiviral compounds including neutralizing antibodies that effectively prevent or treat this disease. Methods The human synthetic single-chain fragment variable (scFv ETH-2 phage antibody library was used for the isolation of scFvs against the nucleocapsid (N protein of SARS-CoV using a bio panning-based strategy. The selected scFvs were characterized under genetics-molecular aspects and for SARS-CoV N protein detection in ELISA, western blotting and immunocytochemistry. Results Human scFv antibodies to N protein of SARS-CoV can be easily isolated by selecting the ETH-2 phage library on immunotubes coated with antigen. These in vitro selected human scFvs specifically recognize in ELISA and western blotting studies distinct epitopes in N protein domains and detect in immunohistochemistry investigations SARS-CoV particles in infected Vero cells. Conclusion The human scFv antibodies isolated and described in this study represent useful reagents for rapid detection of N SARS-CoV protein and SARS virus particles in infected target cells.

Distinct patterns of IFITM-mediated restriction of filoviruses, SARS coronavirus, and influenza A virus.

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I-Chueh Huang

2011-01-01

Full Text Available Interferon-inducible transmembrane proteins 1, 2, and 3 (IFITM1, 2, and 3 are recently identified viral restriction factors that inhibit infection mediated by the influenza A virus (IAV hemagglutinin (HA protein. Here we show that IFITM proteins restricted infection mediated by the entry glycoproteins (GP(1,2 of Marburg and Ebola filoviruses (MARV, EBOV. Consistent with these observations, interferon-β specifically restricted filovirus and IAV entry processes. IFITM proteins also inhibited replication of infectious MARV and EBOV. We observed distinct patterns of IFITM-mediated restriction: compared with IAV, the entry processes of MARV and EBOV were less restricted by IFITM3, but more restricted by IFITM1. Moreover, murine Ifitm5 and 6 did not restrict IAV, but efficiently inhibited filovirus entry. We further demonstrate that replication of infectious SARS coronavirus (SARS-CoV and entry mediated by the SARS-CoV spike (S protein are restricted by IFITM proteins. The profile of IFITM-mediated restriction of SARS-CoV was more similar to that of filoviruses than to IAV. Trypsin treatment of receptor-associated SARS-CoV pseudovirions, which bypasses their dependence on lysosomal cathepsin L, also bypassed IFITM-mediated restriction. However, IFITM proteins did not reduce cellular cathepsin activity or limit access of virions to acidic intracellular compartments. Our data indicate that IFITM-mediated restriction is localized to a late stage in the endocytic pathway. They further show that IFITM proteins differentially restrict the entry of a broad range of enveloped viruses, and modulate cellular tropism independently of viral receptor expression.

Genetic analysis of the SARS-coronavirus spike glycoprotein functional domains involved in cell-surface expression and cell-to-cell fusion

International Nuclear Information System (INIS)

Petit, Chad M.; Melancon, Jeffrey M.; Chouljenko, Vladimir N.; Colgrove, Robin; Farzan, Michael; Knipe, David M.; Kousoulas, K.G.

2005-01-01

The SARS-coronavirus (SARS-CoV) is the etiological agent of severe acute respiratory syndrome (SARS). The SARS-CoV spike (S) glycoprotein mediates membrane fusion events during virus entry and virus-induced cell-to-cell fusion. To delineate functional domains of the SARS-CoV S glycoprotein, single point mutations, cluster-to-lysine and cluster-to-alanine mutations, as well as carboxyl-terminal truncations were investigated in transient expression experiments. Mutagenesis of either the coiled-coil domain of the S glycoprotein amino terminal heptad repeat, the predicted fusion peptide, or an adjacent but distinct region, severely compromised S-mediated cell-to-cell fusion, while intracellular transport and cell-surface expression were not adversely affected. Surprisingly, a carboxyl-terminal truncation of 17 amino acids substantially increased S glycoprotein-mediated cell-to-cell fusion suggesting that the terminal 17 amino acids regulated the S fusogenic properties. In contrast, truncation of 26 or 39 amino acids eliminating either one or both of the two endodomain cysteine-rich motifs, respectively, inhibited cell fusion in comparison to the wild-type S. The 17 and 26 amino-acid deletions did not adversely affect S cell-surface expression, while the 39 amino-acid truncation inhibited S cell-surface expression suggesting that the membrane proximal cysteine-rich motif plays an essential role in S cell-surface expression. Mutagenesis of the acidic amino-acid cluster in the carboxyl terminus of the S glycoprotein as well as modification of a predicted phosphorylation site within the acidic cluster revealed that this amino-acid motif may play a functional role in the retention of S at cell surfaces. This genetic analysis reveals that the SARS-CoV S glycoprotein contains extracellular domains that regulate cell fusion as well as distinct endodomains that function in intracellular transport, cell-surface expression, and cell fusion

Broadening of neutralization activity to directly block a dominant antibody-driven SARS-coronavirus evolution pathway.

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Jianhua Sui

2008-11-01

Full Text Available Phylogenetic analyses have provided strong evidence that amino acid changes in spike (S protein of animal and human SARS coronaviruses (SARS-CoVs during and between two zoonotic transfers (2002/03 and 2003/04 are the result of positive selection. While several studies support that some amino acid changes between animal and human viruses are the result of inter-species adaptation, the role of neutralizing antibodies (nAbs in driving SARS-CoV evolution, particularly during intra-species transmission, is unknown. A detailed examination of SARS-CoV infected animal and human convalescent sera could provide evidence of nAb pressure which, if found, may lead to strategies to effectively block virus evolution pathways by broadening the activity of nAbs. Here we show, by focusing on a dominant neutralization epitope, that contemporaneous- and cross-strain nAb responses against SARS-CoV spike protein exist during natural infection. In vitro immune pressure on this epitope using 2002/03 strain-specific nAb 80R recapitulated a dominant escape mutation that was present in all 2003/04 animal and human viruses. Strategies to block this nAb escape/naturally occurring evolution pathway by generating broad nAbs (BnAbs with activity against 80R escape mutants and both 2002/03 and 2003/04 strains were explored. Structure-based amino acid changes in an activation-induced cytidine deaminase (AID "hot spot" in a light chain CDR (complementarity determining region alone, introduced through shuffling of naturally occurring non-immune human VL chain repertoire or by targeted mutagenesis, were successful in generating these BnAbs. These results demonstrate that nAb-mediated immune pressure is likely a driving force for positive selection during intra-species transmission of SARS-CoV. Somatic hypermutation (SHM of a single VL CDR can markedly broaden the activity of a strain-specific nAb. The strategies investigated in this study, in particular the use of structural

Immunogenicity of recombinant feline infectious peritonitis virus spike protein in mice and kittens

NARCIS (Netherlands)

Horzinek, M.C.; Vennema, H.; Groot, R. de; Harbour, D.A.; Dalderup, M.; Gruffydd-Jones, T.; Spaan, W.J.M.

1990-01-01

The gene encoding the fusogenic spike protein of the coronavirus causing feline infectious peritonitis (FIVP) was recombined into the genome of vaccinia virus, strain WR. The recombinant induced spike protein specific, in vitro neutralizing antibodies in mkice. When kittens were immunized with the

Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor.

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Ge, Xing-Yi; Li, Jia-Lu; Yang, Xing-Lou; Chmura, Aleksei A; Zhu, Guangjian; Epstein, Jonathan H; Mazet, Jonna K; Hu, Ben; Zhang, Wei; Peng, Cheng; Zhang, Yu-Ji; Luo, Chu-Ming; Tan, Bing; Wang, Ning; Zhu, Yan; Crameri, Gary; Zhang, Shu-Yi; Wang, Lin-Fa; Daszak, Peter; Shi, Zheng-Li

2013-11-28

The 2002-3 pandemic caused by severe acute respiratory syndrome coronavirus (SARS-CoV) was one of the most significant public health events in recent history. An ongoing outbreak of Middle East respiratory syndrome coronavirus suggests that this group of viruses remains a key threat and that their distribution is wider than previously recognized. Although bats have been suggested to be the natural reservoirs of both viruses, attempts to isolate the progenitor virus of SARS-CoV from bats have been unsuccessful. Diverse SARS-like coronaviruses (SL-CoVs) have now been reported from bats in China, Europe and Africa, but none is considered a direct progenitor of SARS-CoV because of their phylogenetic disparity from this virus and the inability of their spike proteins to use the SARS-CoV cellular receptor molecule, the human angiotensin converting enzyme II (ACE2). Here we report whole-genome sequences of two novel bat coronaviruses from Chinese horseshoe bats (family: Rhinolophidae) in Yunnan, China: RsSHC014 and Rs3367. These viruses are far more closely related to SARS-CoV than any previously identified bat coronaviruses, particularly in the receptor binding domain of the spike protein. Most importantly, we report the first recorded isolation of a live SL-CoV (bat SL-CoV-WIV1) from bat faecal samples in Vero E6 cells, which has typical coronavirus morphology, 99.9% sequence identity to Rs3367 and uses ACE2 from humans, civets and Chinese horseshoe bats for cell entry. Preliminary in vitro testing indicates that WIV1 also has a broad species tropism. Our results provide the strongest evidence to date that Chinese horseshoe bats are natural reservoirs of SARS-CoV, and that intermediate hosts may not be necessary for direct human infection by some bat SL-CoVs. They also highlight the importance of pathogen-discovery programs targeting high-risk wildlife groups in emerging disease hotspots as a strategy for pandemic preparedness.

Identification of NCAM that interacts with the PHE-CoV spike protein.

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Gao, Wei; He, Wenqi; Zhao, Kui; Lu, Huijun; Ren, Wenzhi; Du, Chongtao; Chen, Keyan; Lan, Yungang; Song, Deguang; Gao, Feng

2010-09-24

The spike proteins of coronaviruses associate with cellular molecules to mediate infection of their target cells. The characterization of cellular proteins required for virus infection is essential for understanding viral life cycles and may provide cellular targets for antiviral therapies. We identified Neural Cell Adhesion Molecule (NCAM) as a novel interacting partner of the PHE-CoV S protein. A T7 phage display cDNA library from N2a cells was constructed, and the library was screened with the soluble PHE-CoV S glycoproteins. We used a coimmunoprecipitation assay to show that only the NCAM was a binding partner of spike protein. We found that a soluble form of anti-NCAM antibody blocked association of the PHE-CoV with N2a cells. Furthermore, double-stranded siRNA targeted against NCAM inhibited PHE-CoV infection. A novel interaction was identified between NCAM and spike protein and this association is critical during PHE-CoV infection.

Identification of NCAM that interacts with the PHE-CoV spike protein

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Chen Keyan

2010-09-01

Full Text Available Abstract Background The spike proteins of coronaviruses associate with cellular molecules to mediate infection of their target cells. The characterization of cellular proteins required for virus infection is essential for understanding viral life cycles and may provide cellular targets for antiviral therapies. Results We identified Neural Cell Adhesion Molecule (NCAM as a novel interacting partner of the PHE-CoV S protein. A T7 phage display cDNA library from N2a cells was constructed, and the library was screened with the soluble PHE-CoV S glycoproteins. We used a coimmunoprecipitation assay to show that only the NCAM was a binding partner of spike protein. We found that a soluble form of anti-NCAM antibody blocked association of the PHE-CoV with N2a cells. Furthermore, double-stranded siRNA targeted against NCAM inhibited PHE-CoV infection. Conclusions A novel interaction was identified between NCAM and spike protein and this association is critical during PHE-CoV infection.

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

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Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

Identification of the proteins responsible for SAR DNA binding in nuclear matrix of ''Cucurbita pepo''

International Nuclear Information System (INIS)

Rzepecki, R.; Markiewicz, E.; Szopa, J.

1995-01-01

The nuclear matrices from White bush (''Cucurbita pepo var. patisonina'') cell nuclei have been isolated using three methods: I, standard procedure involving extraction of cell nuclei with 2 M NaCl and 1% Triton X-100; II, the same with pre-treatment of cell nuclei with 0.5 mM CuSO 4 (stabilisation step); and III, method with extraction by lithium diiodosalicylate (LIS), and compared the polypeptide pattern. The isolated matrices specifically bind SAR DNA derived from human β-interferon gene in the exogenous SAR binding assay and in the gel mobility shift assay. Using IgG against the 32 kDa endonuclease we have found in the DNA-protein blot assay that this protein is one of the proteins binding SAR DNA. We have identified three proteins with molecular mass of 65 kDa, 60 kDa and 32 kDa which are responsible for SAR DNA binding in the gel mobility shift assay experiments. (author). 21 refs, 3 figs

Spike-based population coding and working memory.

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Martin Boerlin

2011-02-01

Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Analysis of intraviral protein-protein interactions of the SARS coronavirus ORFeome.

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Albrecht von Brunn

2007-05-01

Full Text Available The severe acute respiratory syndrome coronavirus (SARS-CoV genome is predicted to encode 14 functional open reading frames, leading to the expression of up to 30 structural and non-structural protein products. The functions of a large number of viral ORFs are poorly understood or unknown. In order to gain more insight into functions and modes of action and interaction of the different proteins, we cloned the viral ORFeome and performed a genome-wide analysis for intraviral protein interactions and for intracellular localization. 900 pairwise interactions were tested by yeast-two-hybrid matrix analysis, and more than 65 positive non-redundant interactions, including six self interactions, were identified. About 38% of interactions were subsequently confirmed by CoIP in mammalian cells. Nsp2, nsp8 and ORF9b showed a wide range of interactions with other viral proteins. Nsp8 interacts with replicase proteins nsp2, nsp5, nsp6, nsp7, nsp8, nsp9, nsp12, nsp13 and nsp14, indicating a crucial role as a major player within the replication complex machinery. It was shown by others that nsp8 is essential for viral replication in vitro, whereas nsp2 is not. We show that also accessory protein ORF9b does not play a pivotal role for viral replication, as it can be deleted from the virus displaying normal plaque sizes and growth characteristics in Vero cells. However, it can be expected to be important for the virus-host interplay and for pathogenicity, due to its large number of interactions, by enhancing the global stability of the SARS proteome network, or play some unrealized role in regulating protein-protein interactions. The interactions identified provide valuable material for future studies.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

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Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

Sialic Acid Binding Properties of Soluble Coronavirus Spike (S1 Proteins: Differences between Infectious Bronchitis Virus and Transmissible Gastroenteritis Virus

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Christine Winter

2013-07-01

Full Text Available The spike proteins of a number of coronaviruses are able to bind to sialic acids present on the cell surface. The importance of this sialic acid binding ability during infection is, however, quite different. We compared the spike protein of transmissible gastroenteritis virus (TGEV and the spike protein of infectious bronchitis virus (IBV. Whereas sialic acid is the only receptor determinant known so far for IBV, TGEV requires interaction with its receptor aminopeptidase N to initiate infection of cells. Binding tests with soluble spike proteins carrying an IgG Fc-tag revealed pronounced differences between these two viral proteins. Binding of the IBV spike protein to host cells was in all experiments sialic acid dependent, whereas the soluble TGEV spike showed binding to APN but had no detectable sialic acid binding activity. Our results underline the different ways in which binding to sialoglycoconjugates is mediated by coronavirus spike proteins.

Effect of the Streptococcus agalactiae Virulence Regulator CovR on the Pathogenesis of Urinary Tract Infection.

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Sullivan, Matthew J; Leclercq, Sophie Y; Ipe, Deepak S; Carey, Alison J; Smith, Joshua P; Voller, Nathan; Cripps, Allan W; Ulett, Glen C

2017-02-01

Streptococcus agalactiae can cause urinary tract infection (UTI). The role of the S. agalactiae global virulence regulator, CovR, in UTI pathogenesis is unknown. We used murine and human bladder uroepithelial cell models of UTI and S. agalactiae mutants in covR and related factors, including β-hemolysin/cytolysin (β-h/c), surface-anchored adhesin HvgA, and capsule to study the role of CovR in UTI. We found that covR-deficient serotype III S. agalactiae 874391 was significantly attenuated for colonization in mice and adhesion to uroepithelial cells. Mice infected with covR-deficient S. agalactiae produced less proinflammatory cytokines than those infected with wild-type 874391. Acute cytotoxicity in uroepithelial cells triggered by covR-deficient but not wild-type 874391 was associated with significant caspase 3 activation. Mechanistically, covR mutation significantly altered the expression of several genes in S. agalactiae 874391 that encode key virulence factors, including β-h/c and HvgA, but not capsule. Subsequent mutational analyses revealed that HvgA and capsule, but not the β-h/c, exerted significant effects on colonization of the murine urinary tract in vivo. S. agalactiae CovR promotes bladder infection and inflammation, as well as adhesion to and viability of uroepithelial cells. The pathogenesis of S. agalactiae UTI is complex, multifactorial, and influenced by virulence effects of CovR, HvgA, and capsule. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Three-Dimensional Human Bronchial-Tracheal Epithelial Tissue-Like Assemblies (TLAs) as Hosts for Severe Acute Respiratory Syndrome (SARS)-CoV Infection

Science.gov (United States)

Suderman, M. T.; McCarthy, M.; Mossell, E.; Watts, D. M.; Peters, C. J.; Shope, R.; Goodwin, T. J.

2006-01-01

A three-dimensional (3-D) tissue-like assembly (TLA) of human bronchial-tracheal mesenchymal (HBTC) cells with an overlay of human bronchial epithelial (BEAS-2B) cells was constructed using a NASA Bioreactor to survey the infectivity of SARS-CoV. This TLA was inoculated with a low passage number Urbani strain of SARS-CoV. At selected intervals over a 10-day period, media and cell aliquots of the 3-D TLA were harvested for viral titer assay and for light and electron microscopy examination. All viral titer assays were negative in both BEAS-2B two-dimensional monolayer and TLA. Light microscopy immunohistochemistry demonstrated antigen-antibody reactivity with anti-SARS-CoV polyclonal antibody to spike and nuclear proteins on cell membranes and cytoplasm. Coronavirus Group 2 cross-reactivity was demonstrated by positive reaction to anti-FIPV 1 and anti-FIPV 1 and 2 antibodies. TLA examination by transmission electron microscopy indicated increasing cytoplasmic vacuolation with numerous electron-dense bodies measuring 45 to 270 nm from days 4 through 10. There was no evidence of membrane blebbing, membrane duplication, or fragmentation of organelles in the TLAs. However, progressive disruption of endoplasmic reticulum was observed throughout the cells. Antibody response to SARS-CoV specific spike and nucleocapsid glycoproteins, cross-reactivity with FIPV antibodies, and the cytoplasmic pathology suggests this HBTE TLA model is permissive to SARS-CoV infection.

Structure and inhibition of the SARS coronavirus envelope protein ion channel.

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Konstantin Pervushin

2009-07-01

Full Text Available The envelope (E protein from coronaviruses is a small polypeptide that contains at least one alpha-helical transmembrane domain. Absence, or inactivation, of E protein results in attenuated viruses, due to alterations in either virion morphology or tropism. Apart from its morphogenetic properties, protein E has been reported to have membrane permeabilizing activity. Further, the drug hexamethylene amiloride (HMA, but not amiloride, inhibited in vitro ion channel activity of some synthetic coronavirus E proteins, and also viral replication. We have previously shown for the coronavirus species responsible for severe acute respiratory syndrome (SARS-CoV that the transmembrane domain of E protein (ETM forms pentameric alpha-helical bundles that are likely responsible for the observed channel activity. Herein, using solution NMR in dodecylphosphatidylcholine micelles and energy minimization, we have obtained a model of this channel which features regular alpha-helices that form a pentameric left-handed parallel bundle. The drug HMA was found to bind inside the lumen of the channel, at both the C-terminal and the N-terminal openings, and, in contrast to amiloride, induced additional chemical shifts in ETM. Full length SARS-CoV E displayed channel activity when transiently expressed in human embryonic kidney 293 (HEK-293 cells in a whole-cell patch clamp set-up. This activity was significantly reduced by hexamethylene amiloride (HMA, but not by amiloride. The channel structure presented herein provides a possible rationale for inhibition, and a platform for future structure-based drug design of this potential pharmacological target.

Peptide-Based Membrane Fusion Inhibitors Targeting HCoV-229E Spike Protein HR1 and HR2 Domains

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Shuai Xia

2018-02-01

Full Text Available Human coronavirus 229E (HCoV-229E infection in infants, elderly people, and immunocompromised patients can cause severe disease, thus calling for the development of effective and safe therapeutics to treat it. Here we reported the design, synthesis and characterization of two peptide-based membrane fusion inhibitors targeting HCoV-229E spike protein heptad repeat 1 (HR1 and heptad repeat 2 (HR2 domains, 229E-HR1P and 229E-HR2P, respectively. We found that 229E-HR1P and 229E-HR2P could interact to form a stable six-helix bundle and inhibit HCoV-229E spike protein-mediated cell-cell fusion with IC50 of 5.7 and 0.3 µM, respectively. 229E-HR2P effectively inhibited pseudotyped and live HCoV-229E infection with IC50 of 0.5 and 1.7 µM, respectively. In a mouse model, 229E-HR2P administered intranasally could widely distribute in the upper and lower respiratory tracts and maintain its fusion-inhibitory activity. Therefore, 229E-HR2P is a promising candidate for further development as an antiviral agent for the treatment and prevention of HCoV-229E infection.

Consensus-Based Sorting of Neuronal Spike Waveforms.

Science.gov (United States)

Fournier, Julien; Mueller, Christian M; Shein-Idelson, Mark; Hemberger, Mike; Laurent, Gilles

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained "ground truth" data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data.

Assembly of spikes into coronavirus particles is mediated by the carboxy-terminal domain of the spike protein

NARCIS (Netherlands)

Godeke, G J; de Haan, Cornelis A M; Rossen, J W; Vennema, H; Rottier, P J

The type I glycoprotein S of coronavirus, trimers of which constitute the typical viral spikes, is assembled into virions through noncovalent interactions with the M protein. Here we demonstrate that incorporation is mediated by the short carboxy-terminal segment comprising the transmembrane and

Discovery of novel bat coronaviruses in south China that use the same receptor as MERS coronavirus.

Science.gov (United States)

Luo, Chu-Ming; Wang, Ning; Yang, Xing-Lou; Liu, Hai-Zhou; Zhang, Wei; Li, Bei; Hu, Ben; Peng, Cheng; Geng, Qi-Bin; Zhu, Guang-Jian; Li, Fang; Shi, Zheng-Li

2018-04-18

Middle East respiratory syndrome coronavirus (MERS-CoV) has represented a human health threat since 2012. Although several MERS-related CoVs, which belong to the same species as MERS-CoV, have been identified from bats, they do not use the MERS-CoV receptor, dipeptidyl peptidase 4 (DPP4). Here, we screened 1059 bat samples from at least 30 bat species collected in different regions in south China and identified 89 strains of lineage C betacoronaviruses, including Tylonycteris pachypus HKU4 , Pipistrellus pipistrellus HKU5, and MERS-related CoVs. We sequenced the full-length genomes of two positive samples collected from the great evening bat, Ia io , from Guangdong Province. The two genomes were highly similar and exhibited genomic structures identical to those of other lineage C betacoronaviruses. While they exhibited genome-wide nucleotide identities of only 75.3 to 81.2% with other MERS-related CoVs, their gene-coding regions were highly similar to their counterparts, except in the case of the spike proteins. Further protein--protein interaction assays demonstrated that the spike proteins of these MERS-related CoVs bind to the receptor DPP4. Recombination analysis suggested that the newly discovered MERS-related CoVs might have acquired their spike genes from a DPP4-recognizing bat HKU4. Our study provides further evidence that bats represent the evolutionary origins of MERS-CoV. IMPORTANCE Previous studies suggested that the Middle East respiratory syndrome coronavirus (MERS-CoV) may have originated in bats. However, its evolutionary path from bats to humans remains unclear. In this study, we discovered 89 novel lineage C betacoronaviruses (BetaCoVs) in eight bat species. We provide the evidence of a MERS-related CoV derived from the great evening bat that uses the same host receptor as human MERS-CoV. This virus also provides evidence for a natural recombination event between the bat MERS-related CoV and another bat coronavirus HKU4. Our study expands the host

Image based SAR product simulation for analysis

Science.gov (United States)

Domik, G.; Leberl, F.

1987-01-01

SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

Srv mediated dispersal of streptococcal biofilms through SpeB is observed in CovRS+ strains.

Directory of Open Access Journals (Sweden)

Kristie L Connolly

Full Text Available Group A Streptococcus (GAS is a human specific pathogen capable of causing both mild infections and severe invasive disease. We and others have shown that GAS is able to form biofilms during infection. That is to say, they form a three-dimensional, surface attached structure consisting of bacteria and a multi-component extracellular matrix. The mechanisms involved in regulation and dispersal of these GAS structures are still unclear. Recently we have reported that in the absence of the transcriptional regulator Srv in the MGAS5005 background, the cysteine protease SpeB is constitutively produced, leading to increased tissue damage and decreased biofilm formation during a subcutaneous infection in a mouse model. This was interesting because MGAS5005 has a naturally occurring mutation that inactivates the sensor kinase domain of the two component regulatory system CovRS. Others have previously shown that strains lacking covS are associated with decreased SpeB production due to CovR repression of speB expression. Thus, our results suggest the inactivation of srv can bypass CovR repression and lead to constitutive SpeB production. We hypothesized that Srv control of SpeB production may be a mechanism to regulate biofilm dispersal and provide a mechanism by which mild infection can transition to severe disease through biofilm dispersal. The question remained however, is this mechanism conserved among GAS strains or restricted to the unique genetic makeup of MGAS5005. Here we show that Srv mediated control of SpeB and biofilm dispersal is conserved in the invasive clinical isolates RGAS053 (serotype M1 and MGAS315 (serotype M3, both of which have covS intact. This work provides additional evidence that Srv regulated control of SpeB may mediate biofilm formation and dispersal in diverse strain backgrounds.

Molecular dynamics of Middle East Respiratory Syndrome Coronavirus (MERS CoV) fusion heptad repeat trimers

KAUST Repository

Kandeel, Mahmoud; Al-Taher, Abdulla; Li, Huifang; Schwingenschlö gl, Udo; Alnazawi, Mohamed

2018-01-01

Structural studies related to Middle East Respiratory Syndrome Coronavirus (MERS CoV) infection process are so limited. In this study, molecular dynamics (MD) simulation was carried out to unravel changes in the MERS CoV heptad repeat domains (HRs

Spike protein assembly into the coronavirion: exploring the limits of its sequence requirements

International Nuclear Information System (INIS)

Bosch, Berend Jan; Haan, Cornelis A.M. de; Smits, Saskia L.; Rottier, Peter J.M.

2005-01-01

The coronavirus spike (S) protein, required for receptor binding and membrane fusion, is incorporated into the assembling virion by interactions with the viral membrane (M) protein. Earlier we showed that the ectodomain of the S protein is not involved in this process. Here we further defined the requirements of the S protein for virion incorporation. We show that the cytoplasmic domain, not the transmembrane domain, determines the association with the M protein and suffices to effect the incorporation into viral particles of chimeric spikes as well as of foreign viral glycoproteins. The essential sequence was mapped to the membrane-proximal region of the cytoplasmic domain, which is also known to be of critical importance for the fusion function of the S protein. Consistently, only short C-terminal truncations of the S protein were tolerated when introduced into the virus by targeted recombination. The important role of the about 38-residues cytoplasmic domain in the assembly of and membrane fusion by this approximately 1300 amino acids long protein is discussed

Epitope mapping and biological function analysis of antibodies produced by immunization of mice with an inactivated Chinese isolate of severe acute respiratory syndrome-associated coronavirus (SARS-CoV)

International Nuclear Information System (INIS)

Chou, Te-hui W.; Wang, Shixia; Sakhatskyy, Pavlo V.; Mboudoudjeck, Innocent; Lawrence, John M.; Huang Song; Coley, Scott; Yang Baoan; Li Jiaming; Zhu Qingyu; Lu Shan

2005-01-01

Inactivated severe acute respiratory syndrome-associated coronavirus (SARS-CoV) has been tested as a candidate vaccine against the re-emergence of SARS. In order to understand the efficacy and safety of this approach, it is important to know the antibody specificities generated with inactivated SARS-CoV. In the current study, a panel of twelve monoclonal antibodies (mAbs) was established by immunizing Balb/c mice with the inactivated BJ01 strain of SARS-CoV isolated from the lung tissue of a SARS-infected Chinese patient. These mAbs could recognize SARS-CoV-infected cells by immunofluorescence analysis (IFA). Seven of them were mapped to the specific segments of recombinant spike (S) protein: six on S1 subunit (aa 12-798) and one on S2 subunit (aa 797-1192). High neutralizing titers against SARS-CoV were detected with two mAbs (1A5 and 2C5) targeting at a subdomain of S protein (aa 310-535), consistent with the previous report that this segment of S protein contains the major neutralizing domain. Some of these S-specific mAbs were able to recognize cleaved products of S protein in SARS-CoV-infected Vero E6 cells. None of the remaining five mAbs could recognize either of the recombinant S, N, M, or E antigens by ELISA. This study demonstrated that the inactivated SARS-CoV was able to preserve the immunogenicity of S protein including its major neutralizing domain. The relative ease with which these mAbs were generated against SARS-CoV virions further supports that subunit vaccination with S constructs may also be able to protect animals and perhaps humans. It is somewhat unexpected that no N-specific mAbs were identified albeit anti-N IgG was easily identified in SARS-CoV-infected patients. The availability of this panel of mAbs also provided potentially useful agents with applications in therapy, diagnosis, and basic research of SARS-CoV

Boosted expression of the SARS-CoV nucleocapsid protein in tobacco and its immunogenicity in mice.

Science.gov (United States)

Zheng, Nuoyan; Xia, Ran; Yang, Cuiping; Yin, Bojiao; Li, Yin; Duan, Chengguo; Liang, Liming; Guo, Huishan; Xie, Qi

2009-08-06

Vaccines produced in plant systems are safe and economical; however, the extensive application of plant-based vaccines is mainly hindered by low expression levels of heterologous proteins in plant systems. Here, we demonstrated that the post-transcriptional gene silencing suppressor p19 protein from tomato bushy stunt virus substantially enhanced the transient expression of recombinant SARS-CoV nucleocapsid (rN) protein in Nicotiana benthamiana. The rN protein in the agrobacteria-infiltrated plant leaf accumulated up to a concentration of 79 microg per g fresh leaf weight at 3 days post infiltration. BALB/c mice were intraperitoneally vaccinated with pre-treated plant extract emulsified in Freund's adjuvant. The rN protein-specific IgG in the mouse sera attained a titer about 1:1,800 following three doses of immunization, which suggested effective B-cell maturation and differentiation in mice. Antibodies of the subclasses IgG1 and IgG2a were abundantly present in the mouse sera. During vaccination of rN protein, the expression of IFN-gamma and IL-10 was evidently up-regulated in splenocytes at different time points, while the expression of IL-2 and IL-4 was not. Up to now, this is the first study that plant-expressed recombinant SARS-CoV N protein can induce strong humoral and cellular responses in mice.

Central ions and lateral asparagine/glutamine zippers stabilize the post-fusion hairpin conformation of the SARS coronavirus spike glycoprotein

International Nuclear Information System (INIS)

Duquerroy, Stephane; Vigouroux, Armelle; Rottier, Peter J.M.; Rey, Felix A.; Jan Bosch, Berend

2005-01-01

The coronavirus spike glycoprotein is a class I membrane fusion protein with two characteristic heptad repeat regions (HR1 and HR2) in its ectodomain. Here, we report the X-ray structure of a previously characterized HR1/HR2 complex of the severe acute respiratory syndrome coronavirus spike protein. As expected, the HR1 and HR2 segments are organized in antiparallel orientations within a rod-like molecule. The HR1 helices form an exceptionally long (120 A) internal coiled coil stabilized by hydrophobic and polar interactions. A striking arrangement of conserved asparagine and glutamine residues of HR1 propagates from two central chloride ions, providing hydrogen-bonding 'zippers' that strongly constrain the path of the HR2 main chain, forcing it to adopt an extended conformation at either end of a short HR2 α-helix

Modeling the Structure of SARS 3a Transmembrane Protein Using a ...

Indian Academy of Sciences (India)

Modeling the structure of SARS 3a Transmembrane protein using a ... for the implicit membrane molecular dynamics (MD) simulations. ... The coordinates during the simulation were saved every 500 steps, and were used for analysis. ... the pair list for calculation of nonbonded interactions being updated after every 10 steps.

A NEW SAR CLASSIFICATION SCHEME FOR SEDIMENTS ON INTERTIDAL FLATS BASED ON MULTI-FREQUENCY POLARIMETRIC SAR IMAGERY

Directory of Open Access Journals (Sweden)

W. Wang

2017-11-01

Full Text Available We present a new classification scheme for muddy and sandy sediments on exposed intertidal flats, which is based on synthetic aperture radar (SAR data, and use ALOS-2 (L-band, Radarsat-2 (C-band and TerraSAR-X (X-band fully polarimetric SAR imagery to demonstrate its effectiveness. Four test sites on the German North Sea coast were chosen, which represent typical surface compositions of different sediments, vegetation, and habitats, and of which a large amount of SAR is used for our analyses. Both Freeman-Durden and Cloude-Pottier polarimetric decomposition are utilized, and an additional descriptor called Double-Bounce Eigenvalue Relative Difference (DERD is introduced into the feature sets instead of the original polarimetric intensity channels. The classification is conducted following Random Forest theory, and the results are verified using ground truth data from field campaigns and an existing classification based on optical imagery. In addition, the use of Kennaugh elements for classification purposes is demonstrated using both fully and dual-polarization multi-frequency and multi-temporal SAR data. Our results show that the proposed classification scheme can be applied for the discrimination of muddy and sandy sediments using L-, C-, and X-band SAR images, while SAR imagery acquired at short wavelengths (C- and X-band can also be used to detect more detailed features such as bivalve beds on intertidal flats.

On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

Directory of Open Access Journals (Sweden)

Zhen Xu

2018-03-01

Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

Elevated plasma surfactant protein D (SP-D) levels and a direct correlation with anti-severe acute respiratory syndrome coronavirus-specific IgG antibody in SARS patients

DEFF Research Database (Denmark)

Wu, Y P; Liu, Z H; Wei, R

2009-01-01

Pulmonary SP-D is a defence lectin promoting clearance of viral infections. SP-D is recognized to bind the S protein of SARS-CoV and enhance phagocytosis. Moreover, systemic SP-D is widely used as a biomarker of alveolar integrity. We investigated the relation between plasma SP-D, SARS-type pneum......Pulmonary SP-D is a defence lectin promoting clearance of viral infections. SP-D is recognized to bind the S protein of SARS-CoV and enhance phagocytosis. Moreover, systemic SP-D is widely used as a biomarker of alveolar integrity. We investigated the relation between plasma SP-D, SARS......-type pneumonia and the SARS-specific IgG response. Sixteen patients with SARS, 19 patients with community-acquired pneumonia (CAP) (Streptococcus pneumonia) and 16 healthy control subjects were enrolled in the study. Plasma SP-D and anti-SARS-CoV N protein IgG were measured using ELISA. SP-D was significantly...... elevated in SARS-type pneumonia [median (95% CI), 453 (379-963) ng/ml versus controls 218 (160-362) ng/ml, P protein IgG (r(2) = 0.5995, P = 0.02). The possible re-emergence of SARS or SARS-like infections suggests a need...

A Markovian event-based framework for stochastic spiking neural networks.

Science.gov (United States)

Touboul, Jonathan D; Faugeras, Olivier D

2011-11-01

In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

Polarimetric SAR image classification based on discriminative dictionary learning model

Science.gov (United States)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Prototype Theory Based Feature Representation for PolSAR Images

OpenAIRE

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

2016-01-01

This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4

Science.gov (United States)

El Yazidi, Abdelhadi; Ramonet, Michel; Ciais, Philippe; Broquet, Gregoire; Pison, Isabelle; Abbaris, Amara; Brunner, Dominik; Conil, Sebastien; Delmotte, Marc; Gheusi, Francois; Guerin, Frederic; Hazan, Lynn; Kachroudi, Nesrine; Kouvarakis, Giorgos; Mihalopoulos, Nikolaos; Rivier, Leonard; Serça, Dominique

2018-03-01

This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV), robust extraction of baseline signal (REBS) and standard deviation of the background (SD) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System) Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern France (OPE), a high-mountain observatory in the south-west of France (PDM), a regional marine background site in Crete (FKL) and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS). This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96 % of the spikes manually identified by station managers were successfully detected both in the SD and the

Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4

Directory of Open Access Journals (Sweden)

A. El Yazidi

2018-03-01

Full Text Available This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV, robust extraction of baseline signal (REBS and standard deviation of the background (SD to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern France (OPE, a high-mountain observatory in the south-west of France (PDM, a regional marine background site in Crete (FKL and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS. This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96 % of the spikes manually identified by station managers were successfully detected both in

Cleavage of group 1 coronavirus spike proteins: how furin cleavage is traded off against heparan sulfate binding upon cell culture adaptation

NARCIS (Netherlands)

Haan, de C.A.M.; Haijema, B.J.; Schellen, P.; Wichgers Schreur, P.J.; Lintelo, te E.; Vennema, H.; Rottier, P.J.M.

2008-01-01

A longstanding enigmatic feature of the group 1 coronaviruses is the uncleaved phenotype of their spike protein, an exceptional property among class I fusion proteins. Here, however, we show that some group 1 coronavirus spike proteins carry a furin enzyme recognition motif and can actually be

Mosaic Evolution of the Severe Acute Respiratory Syndrome Coronavirus

Science.gov (United States)

Stavrinides, John; Guttman, David S.

2004-01-01

Severe acute respiratory syndrome (SARS) is a deadly form of pneumonia caused by a novel coronavirus, a viral family responsible for mild respiratory tract infections in a wide variety of animals including humans, pigs, cows, mice, cats, and birds. Analyses to date have been unable to identify the precise origin of the SARS coronavirus. We used Bayesian, neighbor-joining, and split decomposition phylogenetic techniques on the SARS virus replicase, surface spike, matrix, and nucleocapsid proteins to reveal the evolutionary origin of this recently emerging infectious agent. The analyses support a mammalian-like origin for the replicase protein, an avian-like origin for the matrix and nucleocapsid proteins, and a mammalian-avian mosaic origin for the host-determining spike protein. A bootscan recombination analysis of the spike gene revealed high nucleotide identity between the SARS virus and a feline infectious peritonitis virus throughout the gene, except for a 200- base-pair region of high identity to an avian sequence. These data support the phylogenetic analyses and suggest a possible past recombination event between mammalian-like and avian-like parent viruses. This event occurred near a region that has been implicated to be the human receptor binding site and may have been directly responsible for the switch of host of the SARS coronavirus from animals to humans. PMID:14671089

Research on the method of extracting DEM based on GBInSAR

Science.gov (United States)

Yue, Jianping; Yue, Shun; Qiu, Zhiwei; Wang, Xueqin; Guo, Leping

2016-05-01

Precise topographical information has a very important role in geology, hydrology, natural resources survey and deformation monitoring. The extracting DEM technology based on synthetic aperture radar interferometry (InSAR) obtains the three-dimensional elevation of the target area through the phase information of the radar image data. The technology has large-scale, high-precision, all-weather features. By changing track in the location of the ground radar system up and down, it can form spatial baseline. Then we can achieve the DEM of the target area by acquiring image data from different angles. Three-dimensional laser scanning technology can quickly, efficiently and accurately obtain DEM of target area, which can verify the accuracy of DEM extracted by GBInSAR. But research on GBInSAR in extracting DEM of the target area is a little. For lack of theory and lower accuracy problems in extracting DEM based on GBInSAR now, this article conducted research and analysis on its principle deeply. The article extracted the DEM of the target area, combined with GBInSAR data. Then it compared the DEM obtained by GBInSAR with the DEM obtained by three-dimensional laser scan data and made statistical analysis and normal distribution test. The results showed the DEM obtained by GBInSAR was broadly consistent with the DEM obtained by three-dimensional laser scanning. And its accuracy is high. The difference of both DEM approximately obeys normal distribution. It indicated that extracting the DEM of target area based on GBInSAR is feasible and provided the foundation for the promotion and application of GBInSAR.

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

Science.gov (United States)

Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

A spiking neuron circuit based on a carbon nanotube transistor

International Nuclear Information System (INIS)

Chen, C-L; Kim, K; Truong, Q; Shen, A; Li, Z; Chen, Y

2012-01-01

A spiking neuron circuit based on a carbon nanotube (CNT) transistor is presented in this paper. The spiking neuron circuit has a crossbar architecture in which the transistor gates are connected to its row electrodes and the transistor sources are connected to its column electrodes. An electrochemical cell is incorporated in the gate of the transistor by sandwiching a hydrogen-doped poly(ethylene glycol)methyl ether (PEG) electrolyte between the CNT channel and the top gate electrode. An input spike applied to the gate triggers a dynamic drift of the hydrogen ions in the PEG electrolyte, resulting in a post-synaptic current (PSC) through the CNT channel. Spikes input into the rows trigger PSCs through multiple CNT transistors, and PSCs cumulate in the columns and integrate into a ‘soma’ circuit to trigger output spikes based on an integrate-and-fire mechanism. The spiking neuron circuit can potentially emulate biological neuron networks and their intelligent functions. (paper)

Detection and full genome characterization of two beta CoV viruses related to Middle East respiratory syndrome from bats in Italy.

Science.gov (United States)

Moreno, Ana; Lelli, Davide; de Sabato, Luca; Zaccaria, Guendalina; Boni, Arianna; Sozzi, Enrica; Prosperi, Alice; Lavazza, Antonio; Cella, Eleonora; Castrucci, Maria Rita; Ciccozzi, Massimo; Vaccari, Gabriele

2017-12-19

Middle East respiratory syndrome coronavirus (MERS-CoV), which belongs to beta group of coronavirus, can infect multiple host species and causes severe diseases in humans. Multiple surveillance and phylogenetic studies suggest a bat origin. In this study, we describe the detection and full genome characterization of two CoVs closely related to MERS-CoV from two Italian bats, Pipistrellus kuhlii and Hypsugo savii. Pool of viscera were tested by a pan-coronavirus RT-PCR. Virus isolation was attempted by inoculation in different cell lines. Full genome sequencing was performed using the Ion Torrent platform and phylogenetic trees were performed using IQtree software. Similarity plots of CoV clade c genomes were generated by using SSE v1.2. The three dimensional macromolecular structure (3DMMS) of the receptor binding domain (RBD) in the S protein was predicted by sequence-homology method using the protein data bank (PDB). Both samples resulted positive to the pan-coronavirus RT-PCR (IT-batCoVs) and their genome organization showed identical pattern of MERS CoV. Phylogenetic analysis showed a monophyletic group placed in the Beta2c clade formed by MERS-CoV sequences originating from humans and camels and bat-related sequences from Africa, Italy and China. The comparison of the secondary and 3DMMS of the RBD of IT-batCoVs with MERS, HKU4 and HKU5 bat sequences showed two aa deletions located in a region corresponding to the external subdomain of MERS-RBD in IT-batCoV and HKU5 RBDs. This study reported two beta CoVs closely related to MERS that were obtained from two bats belonging to two commonly recorded species in Italy (P. kuhlii and H. savii). The analysis of the RBD showed similar structure in IT-batCoVs and HKU5 respect to HKU4 sequences. Since the RBD domain of HKU4 but not HKU5 can bind to the human DPP4 receptor for MERS-CoV, it is possible to suggest also for IT-batCoVs the absence of DPP4-binding potential. More surveillance studies are needed to better

Coronavirus nucleocapsid proteins assemble constitutively in high molecular oligomers

NARCIS (Netherlands)

Cong, Yingying; Kriegenburg, Franziska; de Haan, Cornelis A. M.; Reggiori, Fulvio

2017-01-01

Coronaviruses (CoV) are enveloped viruses and rely on their nucleocapsid N protein to incorporate the positive-stranded genomic RNA into the virions. CoV N proteins form oligomers but the mechanism and relevance underlying their multimerization remain to be fully understood. Using in vitro pull-down

Síntese de látices com baixa concentração de compostos orgânicos voláteis (COVs: efeito das técnicas de redução dos COVs nas propriedades dos látexes e das tintas

Directory of Open Access Journals (Sweden)

Maurício Pinheiro de Oliveira

2014-08-01

Full Text Available A redução dos compostos orgânicos voláteis (COVs nos látices produzidos via polimerização em emulsão é uma opção viável, mas em algumas situações pode comprometer a qualidade do látex. Diferentes técnicas de redução da concentração dos monômeros e dos COVs foram estudadas com o objetivo de entender o efeito destas técnicas e da concentração dos COVs nas propriedades de aplicação dos látices e das tintas. Os látices de estireno com acrilato de 2-etil hexila funcionalizados com ácido acrílico e acrilamida foram produzidos via polimerização em emulsão, seguido por remoção química, física e a combinação de ambas as técnicas de redução dos monômeros e dos COVs. Os parâmetros relacionados à técnica de redução dos COVs, ao tipo de iniciador, ao agente de redução e à introdução de nitrogênio saturado com vapor de água foram estudados e correlacionados com as propriedades de aplicação das tintas. A combinação da técnica química com a técnica física foi mais eficiente na redução dos monômeros e dos COVs nos látices. As técnicas utilizadas na redução dos COVs tiveram influência negativa nas propriedades de aplicação dos látices. A resistência à abrasão dos filmes de tinta foi dependente da técnica empregada e da concentração dos COVs.

Unsupervised spike sorting based on discriminative subspace learning.

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Transcriptional profiling of Vero E6 cells over-expressing SARS-CoV S2 subunit: Insights on viral regulation of apoptosis and proliferation

International Nuclear Information System (INIS)

Yeung, Y.-S.; Yip, C.-W.; Hon, C.-C.; Chow, Ken Y.C.; Ma, Iris C.M.; Zeng Fanya; Leung, Frederick C.C.

2008-01-01

We have previously demonstrated that over-expression of spike protein (S) of severe acute respiratory syndrome coronavirus (SARS-CoV) or its C-terminal subunit (S2) is sufficient to induce apoptosis in vitro. To further investigate the possible roles of S2 in SARS-CoV-induced apoptosis and pathogenesis of SARS, we characterized the host expression profiles induced upon S2 over-expression in Vero E6 cells by oligonucleotide microarray analysis. Possible activation of mitochondrial apoptotic pathway in S2 expressing cells was suggested, as evidenced by the up-regulation of cytochrome c and down-regulation of the Bcl-2 family anti-apoptotic members. Inhibition of Bcl-2-related anti-apoptotic pathway was further supported by the diminution of S2-induced apoptosis in Vero E6 cells over-expressing Bcl-xL. In addition, modulation of CCN E2 and CDKN 1A implied the possible control of cell cycle arrest at G1/S phase. This study is expected to extend our understanding on the pathogenesis of SARS at a molecular level

Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

Science.gov (United States)

Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

2016-05-01

Fully Polarimetric SAR (PolSAR) data is used for scattering information retrieval from single SAR resolution cell. Single SAR resolution cell may contain contribution from more than one scattering objects. Hence, single or dual polarized data does not provide all the possible scattering information. So, to overcome this problem fully Polarimetric data is used. It was observed in previous study that fully Polarimetric data of different dates provide different scattering values for same object and coefficient of determination obtained from linear regression between volume scattering and aboveground biomass (AGB) shows different values for the SAR dataset of different dates. Scattering values are important input elements for modelling of forest aboveground biomass. In this research work an approach is proposed to get reliable scattering from interferometric pair of fully Polarimetric RADARSAT-2 data. The field survey for data collection was carried out for Barkot forest during November 10th to December 5th, 2014. Stratified random sampling was used to collect field data for circumference at breast height (CBH) and tree height measurement. Field-measured AGB was compared with the volume scattering elements obtained from decomposition modelling of individual PolSAR images and PolInSAR coherency matrix. Yamaguchi 4-component decomposition was implemented to retrieve scattering elements from SAR data. PolInSAR based decomposition was the great challenge in this work and it was implemented with certain assumptions to create Hermitian coherency matrix with co-registered polarimetric interferometric pair of SAR data. Regression analysis between field-measured AGB and volume scattering element obtained from PolInSAR data showed highest (0.589) coefficient of determination. The same regression with volume scattering elements of individual SAR images showed 0.49 and 0.50 coefficients of determination for master and slave images respectively. This study recommends use of

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

Science.gov (United States)

Hu, G. C.; Zhao, Q. H.

2017-09-01

Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

Coronavirus spike-receptor interactions

NARCIS (Netherlands)

Mou, H.

2015-01-01

Coronaviruses cause important diseases in humans and animals. Coronavirus infection starts with the virus binding with its spike proteins to molecules present on the surface of host cells that act as receptors. This spike-receptor interaction is highly specific and determines the virus’ cell, tissue

Feature Fusion Based Road Extraction for HJ-1-C SAR Image

Directory of Open Access Journals (Sweden)

Lu Ping-ping

2014-06-01

Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

An online supervised learning method based on gradient descent for spiking neurons.

Science.gov (United States)

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Expression, purification and antibody preparation of recombinat SARS-CoV X5 protein].

Science.gov (United States)

Wang, Li-Na; Kong, Jian-Qiang; Zhu, Ping; Du, Guan-Hua; Wang, Wei; Cheng, Ke-Di

2008-11-01

X5 protein is one of the putative unknown proteins of SARS-CoV. The recombinant protein has been successfully expressed in E. coli in the form of insoluble inclusion body. The inclusion body was dissolved in high concentration of urea. Affinity Chromatography was preformed to purify the denatured protein, and then the product was refolded in a series of gradient solutions of urea. The purified protein was obtained with the purity of > 95% and the yield of 93.3 mg x L(-1). Polyclonal antibody of this protein was obtained, and Western blotting assay indicated that the X5 protein has the strong property of antigen. Sixty-eight percent of the recombinant protein sequence was confirmed by LC-ESI-MS/MS analysis.

Target discrimination method for SAR images based on semisupervised co-training

Science.gov (United States)

Wang, Yan; Du, Lan; Dai, Hui

2018-01-01

Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

Directory of Open Access Journals (Sweden)

Fernando Perez-Peña

2013-11-01

Full Text Available In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM. All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6 and power requirements (3.4 W to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6. It also evidences the suitable use of AER as a communication protocol between processing and actuation.

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

Science.gov (United States)

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation. PMID:24264330

Reverse genetics of SARS-related coronavirus using vaccinia virus-based recombination.

Directory of Open Access Journals (Sweden)

Sjoerd H E van den Worm

Full Text Available Severe acute respiratory syndrome (SARS is a zoonotic disease caused by SARS-related coronavirus (SARS-CoV that emerged in 2002 to become a global health concern. Although the original outbreak was controlled by classical public health measures, there is a real risk that another SARS-CoV could re-emerge from its natural reservoir, either in its original form or as a more virulent or pathogenic strain; in which case, the virus would be difficult to control in the absence of any effective antiviral drugs or vaccines. Using the well-studied SARS-CoV isolate HKU-39849, we developed a vaccinia virus-based SARS-CoV reverse genetic system that is both robust and biosafe. The SARS-CoV genome was cloned in separate vaccinia virus vectors, (vSARS-CoV-5prime and vSARS-CoV-3prime as two cDNAs that were subsequently ligated to create a genome-length SARS-CoV cDNA template for in vitro transcription of SARS-CoV infectious RNA transcripts. Transfection of the RNA transcripts into permissive cells led to the recovery of infectious virus (recSARS-CoV. Characterization of the plaques produced by recSARS-CoV showed that they were similar in size to the parental SARS-CoV isolate HKU-39849 but smaller than the SARS-CoV isolate Frankfurt-1. Comparative analysis of replication kinetics showed that the kinetics of recSARS-CoV replication are similar to those of SARS-CoV Frankfurt-1, although the titers of virus released into the culture supernatant are approximately 10-fold less. The reverse genetic system was finally used to generate a recSARS-CoV reporter virus expressing Renilla luciferase in order to facilitate the analysis of SARS-CoV gene expression in human dendritic cells (hDCs. In parallel, a Renilla luciferase gene was also inserted into the genome of human coronavirus 229E (HCoV-229E. Using this approach, we demonstrate that, in contrast to HCoV-229E, SARS-CoV is not able to mediate efficient heterologous gene expression in hDCs.

Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

Directory of Open Access Journals (Sweden)

Xiangguang Leng

2017-08-01

Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

Transient oligomerization of the SARS-CoV N protein--implication for virus ribonucleoprotein packaging.

Science.gov (United States)

Chang, Chung-ke; Chen, Chia-Min Michael; Chiang, Ming-hui; Hsu, Yen-lan; Huang, Tai-huang

2013-01-01

The nucleocapsid (N) phosphoprotein of the severe acute respiratory syndrome coronavirus (SARS-CoV) packages the viral genome into a helical ribonucleocapsid and plays a fundamental role during viral self-assembly. The N protein consists of two structural domains interspersed between intrinsically disordered regions and dimerizes through the C-terminal structural domain (CTD). A key activity of the protein is the ability to oligomerize during capsid formation by utilizing the dimer as a building block, but the structural and mechanistic bases of this activity are not well understood. By disulfide trapping technique we measured the amount of transient oligomers of N protein mutants with strategically located cysteine residues and showed that CTD acts as a primary transient oligomerization domain in solution. The data is consistent with the helical oligomer packing model of N protein observed in crystal. A systematic study of the oligomerization behavior revealed that altering the intermolecular electrostatic repulsion through changes in solution salt concentration or phosphorylation-mimicking mutations affects oligomerization propensity. We propose a biophysical mechanism where electrostatic repulsion acts as a switch to regulate N protein oligomerization.

Protein and Carbohydrate Accumulation in Normal and High-Lysine Barley in Spike Culture

DEFF Research Database (Denmark)

Mather, D.E; Giese, Nanna Henriette

1984-01-01

Spikes of barley cv. Bomi and high-lysine mutants Riso 1508 and Riso 56 were cultured on liquid media at varying N and sucrose levels. Bomi accumulated N in response to increasing N levels in the medium and a higher level was reached than in spikes of intact plants. The distribution of N in salt......-soluble, hordein, and non-protein N fractions appeared to be normal. Endosperm dry weight and starch were lower than in intact plants and declined at higher N levels. A linear relationship was observed between starch content and the concentration of sucrose in the endosperm water. Uptake of culture medium...

Training spiking neural networks to associate spatio-temporal input-output spike patterns

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2013-01-01

In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

NParCov3: A SAS/IML Macro for Nonparametric Randomization-Based Analysis of Covariance

Directory of Open Access Journals (Sweden)

Richard C. Zink

2012-07-01

Full Text Available Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is a reduction of variance for the treatment effect which provides more powerful statistical tests and more precise confidence intervals. Second, it provides estimates of the treatment effect which are adjusted for random imbalances of covariates between the treatment groups. The nonparametric analysis of covariance method of Koch, Tangen, Jung, and Amara (1998 defines a very general methodology using weighted least-squares to generate covariate-adjusted treatment effects with minimal assumptions. This methodology is general in its applicability to a variety of outcomes, whether continuous, binary, ordinal, incidence density or time-to-event. Further, its use has been illustrated in many clinical trial settings, such as multi-center, dose-response and non-inferiority trials.NParCov3 is a SAS/IML macro written to conduct the nonparametric randomization-based covariance analyses of Koch et al. (1998. The software can analyze a variety of outcomes and can account for stratification. Data from multiple clinical trials will be used for illustration.

Evidence of rock slope breathing using ground-based InSAR

Science.gov (United States)

Rouyet, Line; Kristensen, Lene; Derron, Marc-Henri; Michoud, Clément; Blikra, Lars Harald; Jaboyedoff, Michel; Lauknes, Tom Rune

2017-07-01

Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) campaigns were performed in summer 2011 and 2012 in the Romsdalen valley (Møre & Romsdal county, western Norway) in order to assess displacements on Mannen/Børa rock slope. Located 1 km northwest, a second GB-InSAR system continuously monitors the large Mannen rockslide. The availability of two GB-InSAR positions creates a wide coverage of the rock slope, including a slight dataset overlap valuable for validation. A phenomenon of rock slope breathing is detected in a remote and hard-to-access area in mid-slope. Millimetric upward displacements are recorded in August 2011. Analysis of 2012 GB-InSAR campaign, combined with the large dataset from the continuous station, shows that the slope is affected by inflation/deflation phenomenon between 5 and 10 mm along the line-of-sight. The pattern is not homogenous in time and inversions of movement have a seasonal recurrence. These seasonal changes are confirmed by satellite InSAR observations and can possibly be caused by hydrogeological variations. In addition, combination of GB-InSAR results, in situ measurements and satellite InSAR analyses contributes to a better overview of movement distribution over the whole area.

Operational SAR-based sea ice drift monitoring over the Baltic Sea

Directory of Open Access Journals (Sweden)

J. Karvonen

2012-07-01

Full Text Available An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

Mechanisms of Coronavirus Cell Entry Mediated by the Viral Spike Protein

Directory of Open Access Journals (Sweden)

Gary R. Whittaker

2012-06-01

Full Text Available Coronaviruses are enveloped positive-stranded RNA viruses that replicate in the cytoplasm. To deliver their nucleocapsid into the host cell, they rely on the fusion of their envelope with the host cell membrane. The spike glycoprotein (S mediates virus entry and is a primary determinant of cell tropism and pathogenesis. It is classified as a class I fusion protein, and is responsible for binding to the receptor on the host cell as well as mediating the fusion of host and viral membranes—A process driven by major conformational changes of the S protein. This review discusses coronavirus entry mechanisms focusing on the different triggers used by coronaviruses to initiate the conformational change of the S protein: receptor binding, low pH exposure and proteolytic activation. We also highlight commonalities between coronavirus S proteins and other class I viral fusion proteins, as well as distinctive features that confer distinct tropism, pathogenicity and host interspecies transmission characteristics to coronaviruses.

Rapid detection of MERS coronavirus-like viruses in bats: pote1ntial for tracking MERS coronavirus transmission and animal origin.

Science.gov (United States)

Woo, Patrick C Y; Lau, Susanna K P; Chen, Yixin; Wong, Emily Y M; Chan, Kwok-Hung; Chen, Honglin; Zhang, Libiao; Xia, Ningshao; Yuen, Kwok-Yung

2018-03-07

Recently, we developed a monoclonal antibody-based rapid nucleocapsid protein detection assay for diagnosis of MERS coronavirus (MERS-CoV) in humans and dromedary camels. In this study, we examined the usefulness of this assay to detect other lineage C betacoronaviruses closely related to MERS-CoV in bats. The rapid MERS-CoV nucleocapsid protein detection assay was tested positive in 24 (88.9%) of 27 Tylonycteris bat CoV HKU4 (Ty-BatCoV-HKU4) RNA-positive alimentary samples of Tylonycteris pachypus and 4 (19.0%) of 21 Pipistrellus bat CoV HKU5 (Pi-BatCoV-HKU5) RNA-positive alimentary samples of Pipistrellus abramus. There was significantly more Ty-BatCoV-HKU4 RNA-positive alimentary samples than Pi-BatCoV-HKU5 RNA-positive alimentary samples that were tested positive by the rapid MERS-CoV nucleocapsid protein detection assay (P < 0.001 by Chi-square test). The rapid assay was tested negative in all 51 alimentary samples RNA-positive for alphacoronaviruses (Rhinolophus bat CoV HKU2, Myotis bat CoV HKU6, Miniopterus bat CoV HKU8 and Hipposideros batCoV HKU10) and 32 alimentary samples positive for lineage B (SARS-related Rhinolophus bat CoV HKU3) and lineage D (Rousettus bat CoV HKU9) betacoronaviruses. No significant difference was observed between the viral loads of Ty-BatCoV-HKU4/Pi-BatCoV-HKU5 RNA-positive alimentary samples that were tested positive and negative by the rapid test (Mann-Witney U test). The rapid MERS-CoV nucleocapsid protein detection assay is able to rapidly detect lineage C betacoronaviruses in bats. It detected significantly more Ty-BatCoV-HKU4 than Pi-BatCoV-HKU5 because MERS-CoV is more closely related to Ty-BatCoV-HKU4 than Pi-BatCoV-HKU5. This assay will facilitate rapid on-site mass screening of animal samples for ancestors of MERS-CoV and tracking transmission in the related bat species.

Superior Cycle Stability Performance of Quasi-Cuboidal CoV2O6 Microstructures as Electrode Material for Supercapacitors.

Science.gov (United States)

Wang, Yucheng; Chai, Hui; Dong, Hong; Xu, Jiayu; Jia, Dianzeng; Zhou, Wanyong

2016-10-12

In this study, a rapid, facile, and environment-friendly microwave-assisted method followed by annealing for synthesizing the quasi-cuboidal CoV 2 O 6 is developed. The as-prepared samples manifest high supercapacitor properties with a specific capacitance of 223 F g -1 , good rate capability, and superior cycle stability, retaining 123.3% capacitance when the number of cycles reaches 15,000 after determined by electrochemical tests. More importantly, the quasi-cuboidal CoV 2 O 6 for the first time is introduced into the supercapacitor as a kind of electrode material. The superior electrochemical performance of the quasi-cuboidal CoV 2 O 6 will render the metal vanadium oxides as new and attractive active material for promising application in supercapacitors.

Yeast based small molecule screen for inhibitors of SARS-CoV.

Directory of Open Access Journals (Sweden)

Matthew Frieman

Full Text Available Severe acute respiratory coronavirus (SARS-CoV emerged in 2002, resulting in roughly 8000 cases worldwide and 10% mortality. The animal reservoirs for SARS-CoV precursors still exist and the likelihood of future outbreaks in the human population is high. The SARS-CoV papain-like protease (PLP is an attractive target for pharmaceutical development because it is essential for virus replication and is conserved among human coronaviruses. A yeast-based assay was established for PLP activity that relies on the ability of PLP to induce a pronounced slow-growth phenotype when expressed in S. cerevisiae. Induction of the slow-growth phenotype was shown to take place over a 60-hour time course, providing the basis for conducting a screen for small molecules that restore growth by inhibiting the function of PLP. Five chemical suppressors of the slow-growth phenotype were identified from the 2000 member NIH Diversity Set library. One of these, NSC158362, potently inhibited SARS-CoV replication in cell culture without toxic effects on cells, and it specifically inhibited SARS-CoV replication but not influenza virus replication. The effect of NSC158362 on PLP protease, deubiquitinase and anti-interferon activities was investigated but the compound did not alter these activities. Another suppressor, NSC158011, demonstrated the ability to inhibit PLP protease activity in a cell-based assay. The identification of these inhibitors demonstrated a strong functional connection between the PLP-based yeast assay, the inhibitory compounds, and SARS-CoV biology. Furthermore the data with NSC158362 suggest a novel mechanism for inhibition of SARS-CoV replication that may involve an unknown activity of PLP, or alternatively a direct effect on a cellular target that modifies or bypasses PLP function in yeast and mammalian cells.

Les composés organiques volatils réduction des émissions de COV dans l'industrie

CERN Document Server

2013-01-01

Cet ouvrage propose des solutions techniques et une méthodologie pour réduire les émissions de composés organiques volatils (COV) dans l’atmosphère. Il permet : • de connaître l’impact des COV sur l’environnement et sur la santé, ainsi que les réglementations applicables en France et en Europe ; • de choisir les solutions d’amélioration disponibles (prévention, réduction à la source par secteur industriel, technologies de traitement et méthodes de mesure) ; • d’obtenir les clés pour mett re en place une démarche de réduction des émissions de COV (les étapes et les accompagnements possibles) ; • d’observer des exemples réussis d’investissement dans l’industrie. Cet ouvrage est un outil de travail indispensable pour les entreprises concernées par cett e problématique. Il donne les éléments essentiels pour aborder sereinement une démarche de réduction des émissions de COV. Points forts : • Des données rassemblées par un réseau d’experts spécialisés dans...

False-Positive Results in a Recombinant Severe Acute Respiratory Syndrome-Associated Coronavirus (SARS-CoV) Nucleocapsid Enzyme-Linked Immunosorbent Assay Due to HCoV-OC43 and HCoV-229E Rectified by Western Blotting with Recombinant SARS-CoV Spike Polypeptide

OpenAIRE

Woo, Patrick C. Y.; Lau, Susanna K. P.; Wong, Beatrice H. L.; Chan, Kwok-Hung; Hui, Wai-Ting; Kwan, Grace S. W.; Peiris, J. S. Malik; Couch, Robert B.; Yuen, Kwok-Yung

2004-01-01

Using paired serum samples obtained from patients with illness associated with increases in anti-human coronavirus OC43 (HCoV-OC43) or anti-HCoV-229E antibodies, we examined the possibility of false-positive results detected in a recombinant severe acute respiratory syndrome (SARS)-associated coronavirus (SARS-CoV) nucleocapsid protein immunoglobulin G enzyme-linked immunosorbent assay (ELISA). Three of the 21 and 1 of the 7 convalescent-phase serum samples from persons with increases in anti...

SAR Image Classification Based on Its Texture Features

Institute of Scientific and Technical Information of China (English)

LI Pingxiang; FANG Shenghui

2003-01-01

SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

Science.gov (United States)

Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

2015-04-30

New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Transient oligomerization of the SARS-CoV N protein--implication for virus ribonucleoprotein packaging.

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Chung-ke Chang

Full Text Available The nucleocapsid (N phosphoprotein of the severe acute respiratory syndrome coronavirus (SARS-CoV packages the viral genome into a helical ribonucleocapsid and plays a fundamental role during viral self-assembly. The N protein consists of two structural domains interspersed between intrinsically disordered regions and dimerizes through the C-terminal structural domain (CTD. A key activity of the protein is the ability to oligomerize during capsid formation by utilizing the dimer as a building block, but the structural and mechanistic bases of this activity are not well understood. By disulfide trapping technique we measured the amount of transient oligomers of N protein mutants with strategically located cysteine residues and showed that CTD acts as a primary transient oligomerization domain in solution. The data is consistent with the helical oligomer packing model of N protein observed in crystal. A systematic study of the oligomerization behavior revealed that altering the intermolecular electrostatic repulsion through changes in solution salt concentration or phosphorylation-mimicking mutations affects oligomerization propensity. We propose a biophysical mechanism where electrostatic repulsion acts as a switch to regulate N protein oligomerization.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

Science.gov (United States)

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

Science.gov (United States)

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

Directory of Open Access Journals (Sweden)

Sungho Kim

2016-07-01

Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

Feature-Based Nonlocal Polarimetric SAR Filtering

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Xiaoli Xing

2017-10-01

Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

Roadmap to developing a recombinant coronavirus S protein receptor-binding domain vaccine for severe acute respiratory syndrome

Science.gov (United States)

Jiang, Shibo; Bottazzi, Maria Elena; Du, Lanying; Lustigman, Sara; Tseng, Chien-Te Kent; Curti, Elena; Jones, Kathryn; Zhan, Bin; Hotez, Peter J

2013-01-01

A subunit vaccine, RBD-S, is under development to prevent severe acute respiratory syndrome (SARS) caused by SARS coronavirus (SARS-CoV), which is classified by the US NIH as a category C pathogen. This vaccine is comprised of a recombinant receptor-binding domain (RBD) of the SARS-CoV spike (S) protein and formulated on alum, together with a synthetic glucopyranosyl lipid A. The vaccine would induce neutralizing antibodies without causing Th2-type immunopathology. Vaccine development is being led by the nonprofit product development partnership; Sabin Vaccine Institute and Texas Children’s Hospital Center for Vaccine Development in collaboration with two academic partners (the New York Blood Center and University of Texas Medical Branch); an industrial partner (Immune Design Corporation); and Walter Reed Army Institute of Research. A roadmap for the product development of the RBD-S SARS vaccine is outlined with a goal to manufacture the vaccine for clinical testing within the next 5 years. PMID:23252385

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

Science.gov (United States)

Zenke, Friedemann; Ganguli, Surya

2018-04-13

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Molecular dynamics of Middle East Respiratory Syndrome Coronavirus (MERS CoV) fusion heptad repeat trimers

KAUST Repository

Kandeel, Mahmoud

2018-05-17

Structural studies related to Middle East Respiratory Syndrome Coronavirus (MERS CoV) infection process are so limited. In this study, molecular dynamics (MD) simulation was carried out to unravel changes in the MERS CoV heptad repeat domains (HRs) and factors affecting fusion state HR stability. Results indicated that HR trimer is more rapidly stabilized, having stable system energy and lowest root mean square deviations (RMSDs). While trimers were the predominant active form of CoVs HR, monomers were also discovered in both of viral and cellular membranes. In order to find the differences between S2 monomer and trimer molecular dynamics, S2 monomer were modelled and subjected to MD simulation. In contrast to S2 trimer, S2 monomer was unstable, having high RMSDs with major drifts above 8 Å. Fluctuation of HR residue positions revealed major changes in the C-terminal of HR2 and the linker coil between HR1 and HR2 in both monomer and trimer. Hydrophobic residues at the “a” and “d” positions of HR helices stabilize the whole system, having minimal changes in RMSD. The global distance test and contact area difference scores support instability of MERS CoV S2 monomer. Analysis of HR1-HR2 inter-residue contacts and interaction energy revealed three different energy scales along HR helices. Two strong interaction energies were identified at the start of the HR2 helix and at the C-terminal of HR2. The identified critical residues by MD simulation and residues at a and d position of HR helix were strong stabilizers of HRs recognition.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

Science.gov (United States)

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

Combinatorial synthetic peptide vaccine strategy protects against hypervirulent CovR/S mutant streptococci

DEFF Research Database (Denmark)

Pandey, Manisha; Mortensen, Rasmus; Calcutt, Ainslie

2016-01-01

-mediated killing and enabling ingress of bacteria from a superficial wound to deep tissue.We previously showed that a combination vaccine incorporating J8-DT (conserved peptide vaccine from theM protein) and a recombinant SpyCEP fragment protects against CovR/S mutants. To enhance the vaccine's safety profile, we......), and it would be to the organism's advantage if the host did not induce a strong Ab response against it. However, S2 conjugated to diphtheria toxoid is highly immunogenic and induces Abs that recognize and neutralize SpyCEP. Hence, we describe a two-component peptide vaccine that induces Abs (anti-S2....... This protection correlated with a significant influx of neutrophils to the infection site. The data strongly suggest that the lack of natural immunity to hypervirulent GAS strains in humans could be rectified by this combination vaccine....

The staphylococcal accessory regulator, SarA, is an RNA-binding protein that modulates the mRNA turnover properties of late-exponential and stationary phase Staphylococcus aureus cells

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John M Morrison

2012-03-01

Full Text Available The modulation of mRNA turnover is gaining recognition as a mechanism by which Staphylococcus aureus regulates gene expression, but the factors that orchestrate alterations in transcript degradation are poorly understood. In that regard, we previously found that 138 mRNA species, including the virulence factors protein A (spa and collagen binding protein (cna, are stabilized in a sarA-dependent manner during exponential phase growth, suggesting that SarA protein may directly or indirectly effect the RNA turnover properties of these transcripts. Herein, we expanded our characterization of the effects of sarA on mRNA turnover during late exponential and stationary phases of growth. Results revealed that the locus affects the RNA degradation properties of cells during both growth phases. Further, using gel mobility shift assays and RIP-ChIP, it was found that SarA protein is capable of binding mRNA species that it stabilizes both in vitro and within bacterial cells. Taken together, these results suggest that SarA post-transcriptionally regulates S. aureus gene expression in a manner that involves binding to and consequently altering the mRNA turnover properties of target transcripts.

Empirical wind retrieval model based on SAR spectrum measurements

Science.gov (United States)

Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

ambiguity from polarimetric SAR. A criterion based on the complex correlation coefficient between the VV and VH signals sign is applied to select the wind direction. An additional quality control on the wind speed value retrieved with the spectral method is applied. Here, we use the direction obtained with the spectral method and the backscattered signal for CMOD wind speed estimate. The algorithm described above may be refined by the use of numerous SAR data and wind measurements. In the present preliminary work the first results of SAR images combined with in situ data processing are presented. Our results are compared to the results obtained using previously developed models CMOD, C-2PO for VH polarization and statistical wind retrieval approaches [1]. Acknowledgments. This work is supported by the Russian Foundation of Basic Research (grants 13-05-00852-a). [1] M. Portabella, A. Stoffelen, J. A. Johannessen, Toward an optimal inversion method for synthetic aperture radar wind retrieval, Journal of geophysical research, V. 107, N C8, 2002

The SARS Coronavirus 3a protein causes endoplasmic reticulum stress and induces ligand-independent downregulation of the type 1 interferon receptor.

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Rinki Minakshi

2009-12-01

Full Text Available The Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV is reported to cause apoptosis of infected cells and several of its proteins including the 3a accessory protein, are pro-apoptotic. Since the 3a protein localizes to the endoplasmic reticulum (ER-Golgi compartment, its role in causing ER stress was investigated in transiently transfected cells. Cells expressing the 3a proteins showed ER stress based on activation of genes for the ER chaperones GRP78 and GRP94. Since ER stress can cause differential modulation of the unfolded protein response (UPR, which includes the inositol-requiring enzyme 1 (IRE-1, activating transcription factor 6 (ATF6 and PKR-like ER kinase (PERK pathways, these were individually tested in 3a-expressing cells. Only the PERK pathway was found to be activated in 3a-expressing cells based on (1 increased phosphorylation of eukaryotic initiation factor 2 alpha (eIF2alpha and inhibitory effects of a dominant-negative form of eIF2alpha on GRP78 promoter activity, (2 increased translation of activating transcription factor 4 (ATF4 mRNA, and (3 ATF4-dependent activation of the C/EBP homologous protein (CHOP gene promoter. Activation of PERK affects innate immunity by suppression of type 1 interferon (IFN signaling. The 3a protein was found to induce serine phosphorylation within the IFN alpha-receptor subunit 1 (IFNAR1 degradation motif and to increase IFNAR1 ubiquitination. Confocal microscopic analysis showed increased translocation of IFNAR1 into the lysosomal compartment and flow cytometry showed reduced levels of IFNAR1 in 3a-expressing cells. These results provide further mechanistic details of the pro-apoptotic effects of the SARS-CoV 3a protein, and suggest a potential role for it in attenuating interferon responses and innate immunity.

Combined DEM Extration Method from StereoSAR and InSAR

Science.gov (United States)

Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.

2015-06-01

A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

Directory of Open Access Journals (Sweden)

Anton Civit-Balcells

2012-03-01

Full Text Available In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN, which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

Pains and Gains from China’s Experiences with Emerging Epidemics: From SARS to H7N9

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Pengfei Wei

2016-01-01

Full Text Available Over the recent decades, China experienced several emerging virus outbreaks including those caused by the severe acute respiratory syndrome- (SARS- coronavirus (Cov, H5N1 virus, and H7N9 virus. The SARS tragedy revealed faults in China’s infectious disease prevention system, propelling the Chinese government to enact reforms that enabled better combating of the subsequent H1N1 and H7N9 avian flu epidemics. The system is buttressed by three fundamental, mutually reinforcing components: (1 enduring government administration reforms, including legislation establishing a unified public health emergency management system; (2 prioritized funding for biotechnology and biomedicine industrialization, especially in the areas of pathogen identification, drug production, and the development of vaccines and diagnostics; and (3 increasing investment for public health and establishment of a rapid-response infectious diseases prevention and control system. China is now using its hard-gained experience to support the fight against Ebola in Africa and the Middle East Respiratory Syndrome in its own country.

C-band Joint Active/Passive Dual Polarization Sea Ice Detection

Science.gov (United States)

Keller, M. R.; Gifford, C. M.; Winstead, N. S.; Walton, W. C.; Dietz, J. E.

2017-12-01

A technique for synergistically-combining high-resolution SAR returns with like-frequency passive microwave emissions to detect thin (Radar (SAR) is high resolution (5-100m) but because of cross section ambiguities automated algorithms have had difficulty separating thin ice types from water. The radiometric emissivity of thin ice versus water at microwave frequencies is generally unambiguous in the early stages of ice growth. The method, developed using RADARSAT-2 and AMSR-E data, uses higher-ordered statistics. For the SAR, the COV (coefficient of variation, ratio of standard deviation to mean) has fewer ambiguities between ice and water than cross sections, but breaking waves still produce ice-like signatures for both polarizations. For the radiometer, the PRIC (polarization ratio ice concentration) identifies areas that are unambiguously water. Applying cumulative statistics to co-located COV levels adaptively determines an ice/water threshold. Outcomes from extensive testing with Sentinel and AMSR-2 data are shown in the results. The detection algorithm was applied to the freeze-up in the Beaufort, Chukchi, Barents, and East Siberian Seas in 2015 and 2016, spanning mid-September to early November of both years. At the end of the melt, 6 GHz PRIC values are 5-10% greater than those reported by radiometric algorithms at 19 and 37 GHz. During freeze-up, COV separates grease ice (cross-pol/co-pol SAR ratio corrects for COV deficiencies. In general, the dual-sensor detection algorithm reports 10-15% higher total ice concentrations than operational scatterometer or radiometer algorithms, mostly from ice edge and coastal areas. In conclusion, the algorithm presented combines high-resolution SAR returns with passive microwave emissions for automated ice detection at SAR resolutions.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

Science.gov (United States)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

A 16-Channel Nonparametric Spike Detection ASIC Based on EC-PC Decomposition.

Science.gov (United States)

Wu, Tong; Xu, Jian; Lian, Yong; Khalili, Azam; Rastegarnia, Amir; Guan, Cuntai; Yang, Zhi

2016-02-01

In extracellular neural recording experiments, detecting neural spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. In this paper, we report a 16-channel neural spike detection chip based on a customized spike detection method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features a reliable prediction of spikes by applying a probability threshold. The chip takes raw data as input and outputs three data streams simultaneously: field potentials, band-pass filtered neural data, and spiking probability maps. The algorithm parameters are on-chip configured automatically based on input data, which avoids manual parameter tuning. The chip has been tested with both in vivo experiments for functional verification and bench-top experiments for quantitative performance assessment. The system has a total power consumption of 1.36 mW and occupies an area of 6.71 mm (2) for 16 channels. When tested on synthesized datasets with spikes and noise segments extracted from in vivo preparations and scaled according to required precisions, the chip outperforms other detectors. A credit card sized prototype board is developed to provide power and data management through a USB port.

Replication of murine coronavirus requires multiple cysteines in the endodomain of spike protein

International Nuclear Information System (INIS)

Yang, Jinhua; Lv, Jun; Wang, Yuyan; Gao, Shuang; Yao, Qianqian; Qu, Di; Ye, Rong

2012-01-01

A conserved cysteine-rich motif located between the transmembrane domain and the endodomain is essential for membrane fusion and assembly of coronavirus spike (S) protein. Here, we proved that three cysteines within the motif, but not dependent on position, are minimally required for the survival of the recombinant mouse hepatitis virus. When the carboxy termini with these mutated motifs of S proteins were respectively introduced into a heterogeneous protein, both incorporation into lipid rafts and S-palmitoylation of these recombinant proteins showed a similar quantity requirement to cysteine residues. Meanwhile, the redistribution of these proteins on cellular surface indicated that the absence of the positively charged rather than cysteine residues in the motif might lead the dramatic reduction in syncytial formation of some mutants with the deleted motifs. These results suggest that multiple cysteine as well as charged residues concurrently improves the membrane-associated functions of S protein in viral replication and cytopathogenesis.

Replication of murine coronavirus requires multiple cysteines in the endodomain of spike protein

Energy Technology Data Exchange (ETDEWEB)

Yang, Jinhua; Lv, Jun; Wang, Yuyan; Gao, Shuang; Yao, Qianqian; Qu, Di; Ye, Rong, E-mail: yerong24@fudan.edu.cn

2012-06-05

A conserved cysteine-rich motif located between the transmembrane domain and the endodomain is essential for membrane fusion and assembly of coronavirus spike (S) protein. Here, we proved that three cysteines within the motif, but not dependent on position, are minimally required for the survival of the recombinant mouse hepatitis virus. When the carboxy termini with these mutated motifs of S proteins were respectively introduced into a heterogeneous protein, both incorporation into lipid rafts and S-palmitoylation of these recombinant proteins showed a similar quantity requirement to cysteine residues. Meanwhile, the redistribution of these proteins on cellular surface indicated that the absence of the positively charged rather than cysteine residues in the motif might lead the dramatic reduction in syncytial formation of some mutants with the deleted motifs. These results suggest that multiple cysteine as well as charged residues concurrently improves the membrane-associated functions of S protein in viral replication and cytopathogenesis.

SAR-Based Wind Resource Statistics in the Baltic Sea

Directory of Open Access Journals (Sweden)

Alfredo Peña

2011-01-01

Full Text Available Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

Bistatic SAR: Proof of Concept.

Energy Technology Data Exchange (ETDEWEB)

Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

2014-10-01

Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

The SARS coronavirus spike glycoprotein is selectively recognized by lung surfactant protein D and activates macrophages

DEFF Research Database (Denmark)

Leth-Larsen, Rikke; Zhong, Fei; Chow, Vincent T K

2007-01-01

Da glycosylated protein. It was not secreted in the presence of tunicamycin and was detected as a 130 kDa protein in the cell lysate. The purified S-protein bound to Vero but not 293T cells and was itself recognized by lung surfactant protein D (SP-D), a collectin found in the lung alveoli. The binding required...

Synthesis of Salt Soluble Proteins in Barley. Pulse-Labeling Study of Grain Filling in Liquid-Cultured Detached Spikes

DEFF Research Database (Denmark)

Giese, Nanna Henriette; Hejgaard, Jørn

1984-01-01

The accumulation of salt-soluble proteins in the endosperm of developing barley (Hordeum vulgare L.) grains was examined. Detached spikes of barley were cultured at different levels of nitrogen nutrition and pulse-labeled with [14C] sucrose at specific times after anthesis. Proteins were extracted...... to increased nitrogen nutrition. Two major components, β-amylase and protein Z in particular, had a synthesis profile almost identical to that of the endosperm storage protein, hordein....

Long term landslide monitoring with Ground Based SAR

Science.gov (United States)

Monserrat, Oriol; Crosetto, Michele; Luzi, Guido; Gili, Josep; Moya, Jose; Corominas, Jordi

2014-05-01

In the last decade, Ground-Based (GBSAR) has proven to be a reliable microwave Remote Sensing technique in several application fields, especially for unstable slopes monitoring. GBSAR can provide displacement measurements over few squared kilometres areas and with a very high spatial and temporal resolution. This work is focused on the use of GBSAR technique for long term landslide monitoring based on a particular data acquisition configuration, which is called discontinuous GBSAR (D-GBSAR). In the most commonly used GBSAR configuration, the radar is left installed in situ, acquiring data periodically, e.g. every few minutes. Deformations are estimated by processing sets of GBSAR images acquired during several weeks or months, without moving the system. By contrast, in the D-GBSAR the radar is installed and dismounted at each measurement campaign, revisiting a given site periodically. This configuration is useful to monitor slow deformation phenomena. In this work, two alternative ways for exploiting the D-GBSAR technique will be presented: the DInSAR technique and the Amplitude based Technique. The former is based on the exploitation of the phase component of the acquired SAR images and it allows providing millimetric precision on the deformation estimates. However, this technique presents several limitations like the reduction of measurable points with an increase in the period of observation, the ambiguous nature of the phase measurements, and the influence of the atmospheric phase component that can make it non applicable in some cases, specially when working in natural environments. The second approach, that is based on the use of the amplitude component of GB-SAR images combined with a image matching technique, will allow the estimation of the displacements over specific targets avoiding two of the limitations commented above: the phase unwrapping and atmosphere contribution but reducing the deformation measurement precision. Two successful examples of D

Structural Insights into Immune Recognition of the Severe Acute Respiratory Syndrome Coronavirus S Protein Receptor Binding Domain

Energy Technology Data Exchange (ETDEWEB)

Pak, J.; Sharon, C; Satkunarajah, M; Thierry, C; Cameron, C; Kelvin, D; Seetharaman, J; Cochrane, A; Plummer, F; et. al.

2009-01-01

The spike (S) protein of the severe acute respiratory syndrome coronavirus (SARS-CoV) is responsible for host cell attachment and fusion of the viral and host cell membranes. Within S the receptor binding domain (RBD) mediates the interaction with angiotensin-converting enzyme 2 (ACE2), the SARS-CoV host cell receptor. Both S and the RBD are highly immunogenic and both have been found to elicit neutralizing antibodies. Reported here is the X-ray crystal structure of the RBD in complex with the Fab of a neutralizing mouse monoclonal antibody, F26G19, elicited by immunization with chemically inactivated SARS-CoV. The RBD-F26G19 Fab complex represents the first example of the structural characterization of an antibody elicited by an immune response to SARS-CoV or any fragment of it. The structure reveals that the RBD surface recognized by F26G19 overlaps significantly with the surface recognized by ACE2 and, as such, suggests that F26G19 likely neutralizes SARS-CoV by blocking the virus-host cell interaction.

Spike Protein Fusion Peptide and Feline Coronavirus Virulence

Science.gov (United States)

Chang, Hui-Wen; Egberink, Herman F.; Halpin, Rebecca; Spiro, David J.

2012-01-01

Coronaviruses are well known for their potential to change their host or tissue tropism, resulting in unpredictable new diseases and changes in pathogenicity; severe acute respiratory syndrome and feline coronaviruses, respectively, are the most recognized examples. Feline coronaviruses occur as 2 pathotypes: nonvirulent feline enteric coronaviruses (FECVs), which replicate in intestinal epithelium cells, and lethal feline infectious peritonitis viruses (FIPVs), which replicate in macrophages. Evidence indicates that FIPV originates from FECV by mutation, but consistent distinguishing differences have not been established. We sequenced the full genome of 11 viruses of each pathotype and then focused on the single most distinctive site by additionally sequencing hundreds of viruses in that region. As a result, we identified 2 alternative amino acid differences in the putative fusion peptide of the spike protein that together distinguish FIPV from FECV in >95% of cases. By these and perhaps other mutations, the virus apparently acquires its macrophage tropism and spreads systemically. PMID:22709821

The Establishment of the SAR images database System Based on Oracle and ArcSDE

International Nuclear Information System (INIS)

Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

2014-01-01

Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

SARS virus

Indian Academy of Sciences (India)

... consequence.Protein spike similar. HE gene absent. 2787 nucleotides. Largest genome. Jumps species by genetic deletion. < 300 compounds screened. Glycyrrhizin (liquorics/mullatha) seems attractive. Antivirals not effective. Vaccines – animal model only in monkeys. Killed corona or knockout weakened virus as targets.

UAVSAR and TerraSAR-X Based InSAR Detection of Localized Subsidence in the New Orleans Area

Science.gov (United States)

Blom, R. G.; An, K.; Jones, C. E.; Latini, D.

2014-12-01

Vulnerability of the US Gulf coast to inundation has received increased attention since hurricanes Katrina and Rita. Compounding effects of sea level rise, wetland loss, and regional and local subsidence makes flood protection a difficult challenge, and particularly for the New Orleans area. Key to flood protection is precise knowledge of elevations and elevation changes. Analysis of historical and continuing geodetic measurements show surprising complexity, including locations subsiding more rapidly than considered during planning of hurricane protection and coastal restoration projects. Combining traditional, precise geodetic data with interferometric synthetic aperture radar (InSAR) observations can provide geographically dense constraints on surface deformation. The Gulf Coast environment is challenging for InSAR techniques, especially with systems not designed for interferometry. We use two InSAR capable systems, the L- band (24 cm wavelength) airborne JPL/NASA UAVSAR, and the DLR/EADS Astrium spaceborne TerraSAR X-band (3 cm wavelength), and compare results. First, we are applying pair-wise InSAR to the longer wavelength UAVSAR data to detect localized elevation changes potentially impacting flood protection infrastructure from 2009 - 2014. We focus on areas on and near flood protection infrastructure to identify changes indicative of subsidence, structural deformation, and/or seepage. The Spaceborne TerraSAR X-band SAR system has relatively frequent observations, and dense persistent scatterers in urban areas, enabling measurement of very small displacements. We compare L-band UAVSAR results with permanent scatterer (PS-InSAR) and Short Baseline Subsets (SBAS) interferometric analyses of a stack composed by 28 TerraSAR X-band images acquired over the same period. Thus we can evaluate results from the different radar frequencies and analyses techniques. Preliminary results indicate subsidence features potentially of a variety of causes, including ground water

The SARS-unique domain (SUD of SARS coronavirus contains two macrodomains that bind G-quadruplexes.

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Jinzhi Tan

2009-05-01

Full Text Available Since the outbreak of severe acute respiratory syndrome (SARS in 2003, the three-dimensional structures of several of the replicase/transcriptase components of SARS coronavirus (SARS-CoV, the non-structural proteins (Nsps, have been determined. However, within the large Nsp3 (1922 amino-acid residues, the structure and function of the so-called SARS-unique domain (SUD have remained elusive. SUD occurs only in SARS-CoV and the highly related viruses found in certain bats, but is absent from all other coronaviruses. Therefore, it has been speculated that it may be involved in the extreme pathogenicity of SARS-CoV, compared to other coronaviruses, most of which cause only mild infections in humans. In order to help elucidate the function of the SUD, we have determined crystal structures of fragment 389-652 ("SUD(core" of Nsp3, which comprises 264 of the 338 residues of the domain. Both the monoclinic and triclinic crystal forms (2.2 and 2.8 A resolution, respectively revealed that SUD(core forms a homodimer. Each monomer consists of two subdomains, SUD-N and SUD-M, with a macrodomain fold similar to the SARS-CoV X-domain. However, in contrast to the latter, SUD fails to bind ADP-ribose, as determined by zone-interference gel electrophoresis. Instead, the entire SUD(core as well as its individual subdomains interact with oligonucleotides known to form G-quadruplexes. This includes oligodeoxy- as well as oligoribonucleotides. Mutations of selected lysine residues on the surface of the SUD-N subdomain lead to reduction of G-quadruplex binding, whereas mutations in the SUD-M subdomain abolish it. As there is no evidence for Nsp3 entering the nucleus of the host cell, the SARS-CoV genomic RNA or host-cell mRNA containing long G-stretches may be targets of SUD. The SARS-CoV genome is devoid of G-stretches longer than 5-6 nucleotides, but more extended G-stretches are found in the 3'-nontranslated regions of mRNAs coding for certain host-cell proteins

A camel-derived MERS-CoV with a variant spike protein cleavage site and distinct fusion activation properties

Science.gov (United States)

Millet, Jean Kaoru; Goldstein, Monty E; Labitt, Rachael N; Hsu, Hung-Lun; Daniel, Susan; Whittaker, Gary R

2016-01-01

Middle East respiratory syndrome coronavirus (MERS-CoV) continues to circulate in both humans and camels, and the origin and evolution of the virus remain unclear. Here we characterize the spike protein of a camel-derived MERS-CoV (NRCE-HKU205) identified in 2013, early in the MERS outbreak. NRCE-HKU205 spike protein has a variant cleavage motif with regard to the S2′ fusion activation site—notably, a novel substitution of isoleucine for the otherwise invariant serine at the critical P1′ cleavage site position. The substitutions resulted in a loss of furin-mediated cleavage, as shown by fluorogenic peptide cleavage and western blot assays. Cell–cell fusion and pseudotyped virus infectivity assays demonstrated that the S2′ substitutions decreased spike-mediated fusion and viral entry. However, cathepsin and trypsin-like protease activation were retained, albeit with much reduced efficiency compared with the prototypical EMC/2012 human strain. We show that NRCE-HKU205 has more limited fusion activation properties possibly resulting in more restricted viral tropism and may represent an intermediate in the complex pattern of MERS-CoV ecology and evolution. PMID:27999426

Structures of Two Coronavirus Main Proteases: Implications for Substrate Binding and Antiviral Drug Design

Energy Technology Data Exchange (ETDEWEB)

Xue, Xiaoyu; Yu, Hongwei; Yang, Haitao; Xue, Fei; Wu, Zhixin; Shen, Wei; Li, Jun; Zhou, Zhe; Ding, Yi; Zhao, Qi; Zhang, Xuejun C.; Liao, Ming; Bartlam, Mark; Rao, Zihe (SCAU); (Tsinghua); (Chinese Aca. Sci.)

2008-07-21

Coronaviruses (CoVs) can infect humans and multiple species of animals, causing a wide spectrum of diseases. The coronavirus main protease (M{sup pro}), which plays a pivotal role in viral gene expression and replication through the proteolytic processing of replicase polyproteins, is an attractive target for anti-CoV drug design. In this study, the crystal structures of infectious bronchitis virus (IBV) MP{sup pro} and a severe acute respiratory syndrome CoV (SARS-CoV) M{sup pro} mutant (H41A), in complex with an N-terminal autocleavage substrate, were individually determined to elucidate the structural flexibility and substrate binding of M{sup pro}. A monomeric form of IBV M{sup pro} was identified for the first time in CoV M{sup pro} structures. A comparison of these two structures to other available M{sup pro} structures provides new insights for the design of substrate-based inhibitors targeting CoV M{sup pro}s. Furthermore, a Michael acceptor inhibitor (named N3) was cocrystallized with IBV M{sup pro} and was found to demonstrate in vitro inactivation of IBV M{sup pro} and potent antiviral activity against IBV in chicken embryos. This provides a feasible animal model for designing wide-spectrum inhibitors against CoV-associated diseases. The structure-based optimization of N3 has yielded two more efficacious lead compounds, N27 and H16, with potent inhibition against SARS-CoV M{sup pro}.

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

Science.gov (United States)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

Structural bases of coronavirus attachment to host aminopeptidase N and its inhibition by neutralizing antibodies.

Directory of Open Access Journals (Sweden)

Juan Reguera

Full Text Available The coronaviruses (CoVs are enveloped viruses of animals and humans associated mostly with enteric and respiratory diseases, such as the severe acute respiratory syndrome and 10-20% of all common colds. A subset of CoVs uses the cell surface aminopeptidase N (APN, a membrane-bound metalloprotease, as a cell entry receptor. In these viruses, the envelope spike glycoprotein (S mediates the attachment of the virus particles to APN and subsequent cell entry, which can be blocked by neutralizing antibodies. Here we describe the crystal structures of the receptor-binding domains (RBDs of two closely related CoV strains, transmissible gastroenteritis virus (TGEV and porcine respiratory CoV (PRCV, in complex with their receptor, porcine APN (pAPN, or with a neutralizing antibody. The data provide detailed information on the architecture of the dimeric pAPN ectodomain and its interaction with the CoV S. We show that a protruding receptor-binding edge in the S determines virus-binding specificity for recessed glycan-containing surfaces in the membrane-distal region of the pAPN ectodomain. Comparison of the RBDs of TGEV and PRCV to those of other related CoVs, suggests that the conformation of the S receptor-binding region determines cell entry receptor specificity. Moreover, the receptor-binding edge is a major antigenic determinant in the TGEV envelope S that is targeted by neutralizing antibodies. Our results provide a compelling view on CoV cell entry and immune neutralization, and may aid the design of antivirals or CoV vaccines. APN is also considered a target for cancer therapy and its structure, reported here, could facilitate the development of anti-cancer drugs.

Interspike Interval Based Filtering of Directional Selective Retinal Ganglion Cells Spike Trains

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Aurel Vasile Martiniuc

2012-01-01

Full Text Available The information regarding visual stimulus is encoded in spike trains at the output of retina by retinal ganglion cells (RGCs. Among these, the directional selective cells (DSRGC are signaling the direction of stimulus motion. DSRGCs' spike trains show accentuated periods of short interspike intervals (ISIs framed by periods of isolated spikes. Here we use two types of visual stimulus, white noise and drifting bars, and show that short ISI spikes of DSRGCs spike trains are more often correlated to their preferred stimulus feature (that is, the direction of stimulus motion and carry more information than longer ISI spikes. Firstly, our results show that correlation between stimulus and recorded neuronal response is best at short ISI spiking activity and decrease as ISI becomes larger. We then used grating bars stimulus and found that as ISI becomes shorter the directional selectivity is better and information rates are higher. Interestingly, for the less encountered type of DSRGC, known as ON-DSRGC, short ISI distribution and information rates revealed consistent differences when compared with the other directional selective cell type, the ON-OFF DSRGC. However, these findings suggest that ISI-based temporal filtering integrates a mechanism for visual information processing at the output of retina toward higher stages within early visual system.

Identifying SARS-CoV membrane protein amino acid residues linked to virus-like particle assembly.

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Ying-Tzu Tseng

Full Text Available Severe acute respiratory syndrome coronavirus (SARS-CoV membrane (M proteins are capable of self-assembly and release in the form of membrane-enveloped vesicles, and of forming virus-like particles (VLPs when coexpressed with SARS-CoV nucleocapsid (N protein. According to previous deletion analyses, M self-assembly involves multiple M sequence regions. To identify important M amino acid residues for VLP assembly, we coexpressed N with multiple M mutants containing substitution mutations at the amino-terminal ectodomain, carboxyl-terminal endodomain, or transmembrane segments. Our results indicate that a dileucine motif in the endodomain tail (218LL219 is required for efficient N packaging into VLPs. Results from cross-linking VLP analyses suggest that the cysteine residues 63, 85 and 158 are not in close proximity to the M dimer interface. We noted a significant reduction in M secretion due to serine replacement for C158, but not for C63 or C85. Further analysis suggests that C158 is involved in M-N interaction. In addition to mutations of the highly conserved 107-SWWSFNPE-114 motif, substitutions at codons W19, W57, P58, W91, Y94 or F95 all resulted in significantly reduced VLP yields, largely due to defective M secretion. VLP production was not significantly affected by a tryptophan replacement of Y94 or F95 or a phenylalanine replacement of W19, W57 or W91. Combined, these results indicate the involvement of specific M amino acids during SARS-CoV virus assembly, and suggest that aromatic residue retention at specific positions is critical for M function in terms of directing virus assembly.

Curvelet-based compressive sensing for InSAR raw data

Science.gov (United States)

Costa, Marcello G.; da Silva Pinho, Marcelo; Fernandes, David

2015-10-01

The aim of this work is to evaluate the compression performance of SAR raw data for interferometry applications collected by airborne from BRADAR (Brazilian SAR System operating in X and P bands) using the new approach based on compressive sensing (CS) to achieve an effective recovery with a good phase preserving. For this framework is desirable a real-time capability, where the collected data can be compressed to reduce onboard storage and bandwidth required for transmission. In the CS theory, a sparse unknown signals can be recovered from a small number of random or pseudo-random measurements by sparsity-promoting nonlinear recovery algorithms. Therefore, the original signal can be significantly reduced. To achieve the sparse representation of SAR signal, was done a curvelet transform. The curvelets constitute a directional frame, which allows an optimal sparse representation of objects with discontinuities along smooth curves as observed in raw data and provides an advanced denoising optimization. For the tests were made available a scene of 8192 x 2048 samples in range and azimuth in X-band with 2 m of resolution. The sparse representation was compressed using low dimension measurements matrices in each curvelet subband. Thus, an iterative CS reconstruction method based on IST (iterative soft/shrinkage threshold) was adjusted to recover the curvelets coefficients and then the original signal. To evaluate the compression performance were computed the compression ratio (CR), signal to noise ratio (SNR), and because the interferometry applications require more reconstruction accuracy the phase parameters like the standard deviation of the phase (PSD) and the mean phase error (MPE) were also computed. Moreover, in the image domain, a single-look complex image was generated to evaluate the compression effects. All results were computed in terms of sparsity analysis to provides an efficient compression and quality recovering appropriated for inSAR applications

A real-time spike sorting method based on the embedded GPU.

Science.gov (United States)

Zelan Yang; Kedi Xu; Xiang Tian; Shaomin Zhang; Xiaoxiang Zheng

2017-07-01

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

Directory of Open Access Journals (Sweden)

Fan Yang

2015-07-01

Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

Solution structure of the c-terminal dimerization domain of SARS coronavirus nucleocapsid protein solved by the SAIL-NMR method.

Science.gov (United States)

Takeda, Mitsuhiro; Chang, Chung-ke; Ikeya, Teppei; Güntert, Peter; Chang, Yuan-hsiang; Hsu, Yen-lan; Huang, Tai-huang; Kainosho, Masatsune

2008-07-18

The C-terminal domain (CTD) of the severe acute respiratory syndrome coronavirus (SARS-CoV) nucleocapsid protein (NP) contains a potential RNA-binding region in its N-terminal portion and also serves as a dimerization domain by forming a homodimer with a molecular mass of 28 kDa. So far, the structure determination of the SARS-CoV NP CTD in solution has been impeded by the poor quality of NMR spectra, especially for aromatic resonances. We have recently developed the stereo-array isotope labeling (SAIL) method to overcome the size problem of NMR structure determination by utilizing a protein exclusively composed of stereo- and regio-specifically isotope-labeled amino acids. Here, we employed the SAIL method to determine the high-quality solution structure of the SARS-CoV NP CTD by NMR. The SAIL protein yielded less crowded and better resolved spectra than uniform (13)C and (15)N labeling, and enabled the homodimeric solution structure of this protein to be determined. The NMR structure is almost identical with the previously solved crystal structure, except for a disordered putative RNA-binding domain at the N-terminus. Studies of the chemical shift perturbations caused by the binding of single-stranded DNA and mutational analyses have identified the disordered region at the N-termini as the prime site for nucleic acid binding. In addition, residues in the beta-sheet region also showed significant perturbations. Mapping of the locations of these residues onto the helical model observed in the crystal revealed that these two regions are parts of the interior lining of the positively charged helical groove, supporting the hypothesis that the helical oligomer may form in solution.

Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike.

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Thomas A Bowden

Full Text Available The genus Orthobunyavirus within the family Bunyaviridae constitutes an expanding group of emerging viruses, which threaten human and animal health. Despite the medical importance, little is known about orthobunyavirus structure, a prerequisite for understanding virus assembly and entry. Here, using electron cryo-tomography, we report the ultrastructure of Bunyamwera virus, the prototypic member of this genus. Whilst Bunyamwera virions are pleomorphic in shape, they display a locally ordered lattice of glycoprotein spikes. Each spike protrudes 18 nm from the viral membrane and becomes disordered upon introduction to an acidic environment. Using sub-tomogram averaging, we derived a three-dimensional model of the trimeric pre-fusion glycoprotein spike to 3-nm resolution. The glycoprotein spike consists mainly of the putative class-II fusion glycoprotein and exhibits a unique tripod-like arrangement. Protein-protein contacts between neighbouring spikes occur at membrane-proximal regions and intra-spike contacts at membrane-distal regions. This trimeric assembly deviates from previously observed fusion glycoprotein arrangements, suggesting a greater than anticipated repertoire of viral fusion glycoprotein oligomerization. Our study provides evidence of a pH-dependent conformational change that occurs during orthobunyaviral entry into host cells and a blueprint for the structure of this group of emerging pathogens.

Feature discrimination/identification based upon SAR return variations

Science.gov (United States)

Rasco, W. A., Sr.; Pietsch, R.

1978-01-01

A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.

Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

Science.gov (United States)

Zhang, X.; Xiong, B.; Kuang, G.

2018-04-01

In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

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Simon Plank

2014-12-01

Full Text Available In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads—rectangular features of bare land covering an area of approximately 50–60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery and the possibility of detailed land use classification (vs. single-pol SAR. The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59%–71% in each case (area based accuracy assessment. Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74%–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are

Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

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Rong Gui

2016-08-01

Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

Research on Airborne SAR Imaging Based on Esc Algorithm

Science.gov (United States)

Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

2017-09-01

Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

Directory of Open Access Journals (Sweden)

X. T. Dong

2017-09-01

Full Text Available Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC. In this paper, extend chirp scaling algorithm (ECS is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

Characterizing and estimating noise in InSAR and InSAR time series with MODIS

Science.gov (United States)

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

Resolution Enhancement Algorithm for Spaceborn SAR Based on Hanning Function Weighted Sidelobe Suppression

Science.gov (United States)

Li, C.; Zhou, X.; Tang, D.; Zhu, Z.

2018-04-01

Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.

Coronavirus envelope (E) protein remains at the site of assembly

International Nuclear Information System (INIS)

Venkatagopalan, Pavithra; Daskalova, Sasha M.; Lopez, Lisa A.; Dolezal, Kelly A.; Hogue, Brenda G.

2015-01-01

Coronaviruses (CoVs) assemble at endoplasmic reticulum Golgi intermediate compartment (ERGIC) membranes and egress from cells in cargo vesicles. Only a few molecules of the envelope (E) protein are assembled into virions. The role of E in morphogenesis is not fully understood. The cellular localization and dynamics of mouse hepatitis CoV A59 (MHV) E protein were investigated to further understanding of its role during infection. E protein localized in the ERGIC and Golgi with the amino and carboxy termini in the lumen and cytoplasm, respectively. E protein does not traffic to the cell surface. MHV was genetically engineered with a tetracysteine tag at the carboxy end of E. Fluorescence recovery after photobleaching (FRAP) showed that E is mobile in ERGIC/Golgi membranes. Correlative light electron microscopy (CLEM) confirmed the presence of E in Golgi cisternae. The results provide strong support that E proteins carry out their function(s) at the site of budding/assembly. - Highlights: • Mouse hepatitis coronavirus (MHV-CoV) E protein localizes in the ERGIC and Golgi. • MHV-CoV E does not transport to the cell surface. • MHV-CoV can be genetically engineered with a tetracysteine tag appended to E. • First FRAP and correlative light electron microscopy of a CoV E protein. • Live-cell imaging shows that E is mobile in ERGIC/Golgi membranes

Coronavirus envelope (E) protein remains at the site of assembly

Energy Technology Data Exchange (ETDEWEB)

Venkatagopalan, Pavithra [The Biodesign Institute, Center for Infectious Diseases and Vaccinology, Arizona State University, Tempe, AZ 85287-5401 (United States); School of Life Sciences, Arizona State University, Tempe, AZ 85287-5401 (United States); Microbiology Graduate Program, Arizona State University, Tempe, AZ 85287-5401 (United States); Daskalova, Sasha M. [The Biodesign Institute, Center for Infectious Diseases and Vaccinology, Arizona State University, Tempe, AZ 85287-5401 (United States); Department of Biochemistry and Chemistry, Arizona State University, Tempe, AZ 85287-5401 (United States); Lopez, Lisa A. [The Biodesign Institute, Center for Infectious Diseases and Vaccinology, Arizona State University, Tempe, AZ 85287-5401 (United States); School of Life Sciences, Arizona State University, Tempe, AZ 85287-5401 (United States); Molecular and Cellular Biology Graduate Program, Arizona State University, Tempe, AZ 85287-5401 (United States); Dolezal, Kelly A. [The Biodesign Institute, Center for Infectious Diseases and Vaccinology, Arizona State University, Tempe, AZ 85287-5401 (United States); School of Life Sciences, Arizona State University, Tempe, AZ 85287-5401 (United States); Microbiology Graduate Program, Arizona State University, Tempe, AZ 85287-5401 (United States); Hogue, Brenda G., E-mail: Brenda.Hogue@asu.edu [The Biodesign Institute, Center for Infectious Diseases and Vaccinology, Arizona State University, Tempe, AZ 85287-5401 (United States); School of Life Sciences, Arizona State University, Tempe, AZ 85287-5401 (United States)

2015-04-15

Coronaviruses (CoVs) assemble at endoplasmic reticulum Golgi intermediate compartment (ERGIC) membranes and egress from cells in cargo vesicles. Only a few molecules of the envelope (E) protein are assembled into virions. The role of E in morphogenesis is not fully understood. The cellular localization and dynamics of mouse hepatitis CoV A59 (MHV) E protein were investigated to further understanding of its role during infection. E protein localized in the ERGIC and Golgi with the amino and carboxy termini in the lumen and cytoplasm, respectively. E protein does not traffic to the cell surface. MHV was genetically engineered with a tetracysteine tag at the carboxy end of E. Fluorescence recovery after photobleaching (FRAP) showed that E is mobile in ERGIC/Golgi membranes. Correlative light electron microscopy (CLEM) confirmed the presence of E in Golgi cisternae. The results provide strong support that E proteins carry out their function(s) at the site of budding/assembly. - Highlights: • Mouse hepatitis coronavirus (MHV-CoV) E protein localizes in the ERGIC and Golgi. • MHV-CoV E does not transport to the cell surface. • MHV-CoV can be genetically engineered with a tetracysteine tag appended to E. • First FRAP and correlative light electron microscopy of a CoV E protein. • Live-cell imaging shows that E is mobile in ERGIC/Golgi membranes.

Middle east respiratory syndrome coronavirus spike protein delivered by modified vaccinia virus ankara efficiently induces virus-neutralizing antibodies

NARCIS (Netherlands)

F. Song (Fei); R. Fux (Robert); L.B.V. Provacia (Lisette); A. Volz (Asisa); M. Eickmann; S. Becker (Stephan); A.D.M.E. Osterhaus (Albert); B.L. Haagmans (Bart); G. Suttera (Gerd)

2013-01-01

textabstractMiddle East respiratory syndrome coronavirus (MERS-CoV) has recently emerged as a causative agent of severe respiratory disease in humans. Here, we constructed recombinant modified vaccinia virus Ankara (MVA) expressing full-length MERS-CoV spike (S) protein (MVA-MERS-S). The genetic

Unconventional magnetic phase separation in γ -CoV2O6

Science.gov (United States)

Shen, L.; Jellyman, E.; Forgan, E. M.; Blackburn, E.; Laver, M.; Canévet, E.; Schefer, J.; He, Z.; Itoh, M.

2017-08-01

We have explored the magnetism in the nongeometrically frustrated spin-chain system γ -CoV2O6 which possesses a complex magnetic exchange network. Our neutron diffraction patterns at low temperatures (T ≤TN=6.6 K) are best described by a model in which two magnetic phases coexist in a volume ratio 65(1) : 35(1), with each phase consisting of a single spin modulation. This model fits previous studies and our observations better than the model proposed by Lenertz et al. [J. Phys. Chem. C 118, 13981 (2014), 10.1021/jp503389c], which consisted of one phase with two spin modulations. By decreasing the temperature from TN, the minority phase of our model undergoes an incommensurate-commensurate lock-in transition at T*=5.6 K. Based on these results, we propose that phase separation is an alternative approach for degeneracy-lifting in frustrated magnets.

Neuronal spike sorting based on radial basis function neural networks

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Taghavi Kani M

2011-02-01

Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

Pulse-based internal calibration of polarimetric SAR

DEFF Research Database (Denmark)

Dall, Jørgen; Skou, Niels; Christensen, Erik Lintz

1994-01-01

Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops and devel......Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops...

Segment-based change detection for polarimetric SAR data

DEFF Research Database (Denmark)

Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

2006-01-01

that is needed compared to single polarisation SAR to provide reliable and robust detection of changes. Polarimetric SAR data will be available from satellites in the near future, e.g. the Japanese ALOS, the Canadian Radarsat-2 and the German TerraSAR-X. An appropriate way of representing multi-look fully...... be split into a number of smaller fields, a building may be removed from or added to some area, hedgerows may be removed/added or other type of vegetated areas may be partly removed or added. In this case, ambiguities may arise when segments have changed shape and extent from one image to another...

Tie Points Extraction for SAR Images Based on Differential Constraints

Science.gov (United States)

Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

2018-04-01

Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

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J. Tao

2012-09-01

Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

Middle East respiratory syndrome coronavirus (MERS Cov outbreak so far exempted Sub Saharan Africa; is it good news or call for action?

Directory of Open Access Journals (Sweden)

Ballah Akawu Denue

2015-01-01

Full Text Available The reported cases of MERS Cov in Arabian Peninsula and sporadic cases elsewhere except in sub Saharan Africa at present is disquieting considering its initial clinical feature that mimic flu like symptoms caused by other viruses. However MERS Cov is associated with organ dysfunction and high mortality. Although the mode of transmission is still unclear, it is postulated that it spreads through close contact, possibly via respiratory route. High similarities of MERS CoV carried by humans and camels may suggest that the diseases are zoonotic. Furthermore, airborne nosocomial transmission can occur in the room shared by the patients in the hospitals. There is still the confusion of transmission through body fluids or clinical samples, including stools and a cross transmission with medical devices or hands. Currently, all known cases can be directly or indirectly linked to Middle East from where it derives its name. Cases reported outside the Middle East first developed infection in the Middle East and then were exported outside the region. Several hospital-acquired outbreaks that resulted in upsurge of MERS Cov cases in Jeddah revealed lack of systematic implementation of infection prevention and control measures to effectively control emerging infectious diseases. The causative agent is detected and identified using Enzyme Linked Immuunosorbent Assay (ELISA and real-time polymerase chain reaction (RT-PCR that is expensive and not readily available in hospitals located in resource poor settings such as sub Saharan Africa. Although, so far no case of MERS Cov has been reported from sub Saharan Africa, the devastating consequences of MERS epidemic will be more catastrophic if it emerges in developing nations especially in sub Saharan Africa where there are no up to date facilities for investigations and management of such cases. Against this backdrop, we review this hazardous and incurable disease believing that it would create the necessary

An Improved Algorithm to Delineate Urban Targets with Model-Based Decomposition of PolSAR Data

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Dingfeng Duan

2017-10-01

Full Text Available In model-based decomposition algorithms using polarimetric synthetic aperture radar (PolSAR data, urban targets are typically identified based on the existence of strong double-bounced scattering. However, urban targets with large azimuth orientation angles (AOAs produce strong volumetric scattering that appears similar to scattering characteristics from tree canopies. Due to scattering ambiguity, urban targets can be classified into the vegetation category if the same classification scheme of the model-based PolSAR decomposition algorithms is followed. To resolve the ambiguity and to reduce the misclassification eventually, we introduced a correlation coefficient that characterized scattering mechanisms of urban targets with variable AOAs. Then, an existing volumetric scattering model was modified, and a PolSAR decomposition algorithm developed. The validity and effectiveness of the algorithm were examined using four PolSAR datasets. The algorithm was valid and effective to delineate urban targets with a wide range of AOAs, and applicable to a broad range of ground targets from urban areas, and from upland and flooded forest stands.

SAR Imagery Simulation of Ship Based on Electromagnetic Calculations and Sea Clutter Modelling for Classification Applications

International Nuclear Information System (INIS)

Ji, K F; Zhao, Z; Xing, X W; Zou, H X; Zhou, S L

2014-01-01

Ship detection and classification with space-borne SAR has many potential applications within the maritime surveillance, fishery activity management, monitoring ship traffic, and military security. While ship detection techniques with SAR imagery are well established, ship classification is still an open issue. One of the main reasons may be ascribed to the difficulties on acquiring the required quantities of real data of vessels under different observation and environmental conditions with precise ground truth. Therefore, simulation of SAR images with high scenario flexibility and reasonable computation costs is compulsory for ship classification algorithms development. However, the simulation of SAR imagery of ship over sea surface is challenging. Though great efforts have been devoted to tackle this difficult problem, it is far from being conquered. This paper proposes a novel scheme for SAR imagery simulation of ship over sea surface. The simulation is implemented based on high frequency electromagnetic calculations methods of PO, MEC, PTD and GO. SAR imagery of sea clutter is modelled by the representative K-distribution clutter model. Then, the simulated SAR imagery of ship can be produced by inserting the simulated SAR imagery chips of ship into the SAR imagery of sea clutter. The proposed scheme has been validated with canonical and complex ship targets over a typical sea scene

Small heat-shock proteins and leaf cooling capacity account for the unusual heat tolerance of the central spike leaves in Agave tequilana var. Weber.

Science.gov (United States)

Luján, Rosario; Lledías, Fernando; Martínez, Luz María; Barreto, Rita; Cassab, Gladys I; Nieto-Sotelo, Jorge

2009-12-01

Agaves are perennial crassulacean acid metabolism (CAM) plants distributed in tropical and subtropical arid environments, features that are attractive for studying the heat-shock response. In agaves, the stress response can be analysed easily during leaf development, as they form a spirally shaped rosette, having the meristem surrounded by folded leaves in the centre (spike) and the unfolded and more mature leaves in the periphery. Here, we report that the spike of Agave tequilana is the most thermotolerant part of the rosette withstanding shocks of up to 55 degrees C. This finding was inconsistent with the patterns of heat-shock protein (Hsp) gene expression, as maximal accumulation of Hsp transcripts was at 44 degrees C in all sectors (spike, inner, middle and outer). However, levels of small HSP (sHSP)-CI and sHSP-CII proteins were conspicuously higher in spike leaves at all temperatures correlating with their thermotolerance. In addition, spike leaves showed a higher stomatal density and abated more efficiently their temperature several degrees below that of air. We propose that the greater capacity for leaf cooling during the day in response to heat stress, and the elevated levels of sHSPs, constitute part of a set of strategies that protect the SAM and folded leaves of A. tequilana from high temperatures.

Mutations of 3c and spike protein genes correlate with the occurrence of feline infectious peritonitis.

Science.gov (United States)

Bank-Wolf, Barbara Regina; Stallkamp, Iris; Wiese, Svenja; Moritz, Andreas; Tekes, Gergely; Thiel, Heinz-Jürgen

2014-10-10

The genes encoding accessory proteins 3a, 3b, 3c, 7a and 7b, the S2 domain of the spike (S) protein gene and the membrane (M) protein gene of feline infectious peritonitis virus (FIPV) and feline enteric coronavirus (FECV) samples were amplified, cloned and sequenced. For this faeces and/or ascites samples from 19 cats suffering from feline infectious peritonitis (FIP) as well as from 20 FECV-infected healthy cats were used. Sequence comparisons revealed that 3c genes of animals with FIP were heavily affected by nucleotide deletions and point mutations compared to animals infected with FECV; these alterations resulted either in early termination or destruction of the translation initiation codon. Two ascites-derived samples of cats with FIP which displayed no alterations of ORF3c harboured mutations in the S2 domain of the S protein gene which resulted in amino acid exchanges or deletions. Moreover, changes in 3c were often accompanied by mutations in S2. In contrast, in samples obtained from faeces of healthy cats, the ORF3c was never affected by such mutations. Similarly ORF3c from faecal samples of the cats with FIP was mostly intact and showed only in a few cases the same mutations found in the respective ascites samples. The genes encoding 3a, 3b, 7a and 7b displayed no mutations linked to the feline coronavirus (FCoV) biotype. The M protein gene was found to be conserved between FECV and FIPV samples. Our findings suggest that mutations of 3c and spike protein genes correlate with the occurrence of FIP. Copyright © 2014 Elsevier B.V. All rights reserved.

RESOLUTION ENHANCEMENT ALGORITHM FOR SPACEBORN SAR BASED ON HANNING FUNCTION WEIGHTED SIDELOBE SUPPRESSION

Directory of Open Access Journals (Sweden)

C. Li

2018-04-01

Full Text Available Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is −30dB.

Analysis of the effect of mobile phone base station antenna loading on localized SAR and its consequences for measurements.

Science.gov (United States)

Hansson, Björn; Thors, Björn; Törnevik, Christer

2011-12-01

In this work, the effect of antenna element loading on the localized specific absorption rate (SAR) has been analyzed for base station antennas. The analysis was conducted in order to determine whether localized SAR measurements of large multi-element base station antennas can be conducted using standardized procedures and commercially available equipment. More specifically, it was investigated if the antenna shifting measurement procedure, specified in the European base station exposure assessment standard EN 50383, will produce accurate localized SAR results for base station antennas larger than the specified measurement phantom. The obtained results show that SAR accuracy is affected by the presence of lossy material within distances of one wavelength from the tested antennas as a consequence of coupling and redistribution of transmitted power among the antenna elements. It was also found that the existing standardized phantom is not optimal for SAR measurements of large base station antennas. A new methodology is instead proposed based on a larger, box-shaped, whole-body phantom. Copyright © 2011 Wiley Periodicals, Inc.

Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis

Science.gov (United States)

Kojima, S.; Hensley, S.

2012-12-01

There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume

In Situ Tagged nsp15 Reveals Interactions with Coronavirus Replication/Transcription Complex-Associated Proteins

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Jeremiah Athmer

2017-01-01

Full Text Available Coronavirus (CoV replication and transcription are carried out in close proximity to restructured endoplasmic reticulum (ER membranes in replication/transcription complexes (RTC. Many of the CoV nonstructural proteins (nsps are required for RTC function; however, not all of their functions are known. nsp15 contains an endoribonuclease domain that is conserved in the CoV family. While the enzymatic activity and crystal structure of nsp15 are well defined, its role in replication remains elusive. nsp15 localizes to sites of RNA replication, but whether it acts independently or requires additional interactions for its function remains unknown. To begin to address these questions, we created an in situ tagged form of nsp15 using the prototypic CoV, mouse hepatitis virus (MHV. In MHV, nsp15 contains the genomic RNA packaging signal (P/S, a 95-bp RNA stem-loop structure that is not required for viral replication or nsp15 function. Utilizing this knowledge, we constructed an internal hemagglutinin (HA tag that replaced the P/S. We found that nsp15-HA was localized to discrete perinuclear puncta and strongly colocalized with nsp8 and nsp12, both well-defined members of the RTC, but not the membrane (M protein, involved in virus assembly. Finally, we found that nsp15 interacted with RTC-associated proteins nsp8 and nsp12 during infection, and this interaction was RNA independent. From this, we conclude that nsp15 localizes and interacts with CoV proteins in the RTC, suggesting it plays a direct or indirect role in virus replication. Furthermore, the use of in situ epitope tags could be used to determine novel nsp-nsp interactions in coronaviruses.

Automatic spike sorting using tuning information.

Science.gov (United States)

Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

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Manabu Watanabe

2010-01-01

Full Text Available We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR σ∘ under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the σ∘ difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that σ∘ and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

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Shimada Masanobu

2010-01-01

Full Text Available Abstract We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

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X. Xiong

2018-04-01

Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search.

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Chang, Yuan-Jyun; Hwang, Wen-Jyi; Chen, Chih-Chang

2016-12-07

The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO). The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.

Chimeric exchange of coronavirus nsp5 proteases (3CLpro) identifies common and divergent regulatory determinants of protease activity.

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Stobart, Christopher C; Sexton, Nicole R; Munjal, Havisha; Lu, Xiaotao; Molland, Katrina L; Tomar, Sakshi; Mesecar, Andrew D; Denison, Mark R

2013-12-01

Human coronaviruses (CoVs) such as severe acute respiratory syndrome CoV (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV) cause epidemics of severe human respiratory disease. A conserved step of CoV replication is the translation and processing of replicase polyproteins containing 16 nonstructural protein domains (nsp's 1 to 16). The CoV nsp5 protease (3CLpro; Mpro) processes nsp's at 11 cleavage sites and is essential for virus replication. CoV nsp5 has a conserved 3-domain structure and catalytic residues. However, the intra- and intermolecular determinants of nsp5 activity and their conservation across divergent CoVs are unknown, in part due to challenges in cultivating many human and zoonotic CoVs. To test for conservation of nsp5 structure-function determinants, we engineered chimeric betacoronavirus murine hepatitis virus (MHV) genomes encoding nsp5 proteases of human and bat alphacoronaviruses and betacoronaviruses. Exchange of nsp5 proteases from HCoV-HKU1 and HCoV-OC43, which share the same genogroup, genogroup 2a, with MHV, allowed for immediate viral recovery with efficient replication albeit with impaired fitness in direct competition with wild-type MHV. Introduction of MHV nsp5 temperature-sensitive mutations into chimeric HKU1 and OC43 nsp5 proteases resulted in clear differences in viability and temperature-sensitive phenotypes compared with MHV nsp5. These data indicate tight genetic linkage and coevolution between nsp5 protease and the genomic background and identify differences in intramolecular networks regulating nsp5 function. Our results also provide evidence that chimeric viruses within coronavirus genogroups can be used to test nsp5 determinants of function and inhibition in common isogenic backgrounds and cell types.

A Cloud-Based System for Automatic Hazard Monitoring from Sentinel-1 SAR Data

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Meyer, F. J.; Arko, S. A.; Hogenson, K.; McAlpin, D. B.; Whitley, M. A.

2017-12-01

Despite the all-weather capabilities of Synthetic Aperture Radar (SAR), and its high performance in change detection, the application of SAR for operational hazard monitoring was limited in the past. This has largely been due to high data costs, slow product delivery, and limited temporal sampling associated with legacy SAR systems. Only since the launch of ESA's Sentinel-1 sensors have routinely acquired and free-of-charge SAR data become available, allowing—for the first time—for a meaningful contribution of SAR to disaster monitoring. In this paper, we present recent technical advances of the Sentinel-1-based SAR processing system SARVIEWS, which was originally built to generate hazard products for volcano monitoring centers. We outline the main functionalities of SARVIEWS including its automatic database interface to Sentinel-1 holdings of the Alaska Satellite Facility (ASF), and its set of automatic processing techniques. Subsequently, we present recent system improvements that were added to SARVIEWS and allowed for a vast expansion of its hazard services; specifically: (1) In early 2017, the SARVIEWS system was migrated into the Amazon Cloud, providing access to cloud capabilities such as elastic scaling of compute resources and cloud-based storage; (2) we co-located SARVIEWS with ASF's cloud-based Sentinel-1 archive, enabling the efficient and cost effective processing of large data volumes; (3) we integrated SARVIEWS with ASF's HyP3 system (http://hyp3.asf.alaska.edu/), providing functionality such as subscription creation via API or map interface as well as automatic email notification; (4) we automated the production chains for seismic and volcanic hazards by integrating SARVIEWS with the USGS earthquake notification service (ENS) and the USGS eruption alert system. Email notifications from both services are parsed and subscriptions are automatically created when certain event criteria are met; (5) finally, SARVIEWS-generated hazard products are now

Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering.

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Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2014-12-30

Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice. An automatic unsupervised spike sorting method is proposed in this paper. The method uses features extracted by the locality preserving projection (LPP) algorithm. These features afterwards serve as inputs for the landmark-based spectral clustering (LSC) method. Gap statistics (GS) is employed to evaluate the number of clusters before the LSC can be performed. The proposed LPP-LSC is highly accurate and computationally inexpensive spike sorting approach. LPP spike features are very discriminative; thereby boost the performance of clustering methods. Furthermore, the LSC method exhibits its efficiency when integrated with the cluster evaluator GS. The proposed method's accuracy is approximately 13% superior to that of the benchmark combination between wavelet transformation and superparamagnetic clustering (WT-SPC). Additionally, LPP-LSC computing time is six times less than that of the WT-SPC. LPP-LSC obviously demonstrates a win-win spike sorting solution meeting both accuracy and computational cost criteria. LPP and LSC are linear algorithms that help reduce computational burden and thus their combination can be applied into real-time spike analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

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Changyong, Dou; Huadong, Guo; Chunming, Han; yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

2014-03-01

Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc.

Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

International Nuclear Information System (INIS)

Changyong, Dou; Huadong, Guo; Chunming, Han; Yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

2014-01-01

Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc

SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

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Shengli Song

2016-08-01

Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

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Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

The structure of the bacteriophage PRD1 spike sheds light on the evolution of viral capsid architecture.

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Merckel, Michael C; Huiskonen, Juha T; Bamford, Dennis H; Goldman, Adrian; Tuma, Roman

2005-04-15

Comparisons of bacteriophage PRD1 and adenovirus protein structures and virion architectures have been instrumental in unraveling an evolutionary relationship and have led to a proposal of a phylogeny-based virus classification. The structure of the PRD1 spike protein P5 provides further insight into the evolution of viral proteins. The crystallized P5 fragment comprises two structural domains: a globular knob and a fibrous shaft. The head folds into a ten-stranded jelly roll beta barrel, which is structurally related to the tumor necrosis factor (TNF) and the PRD1 coat protein domains. The shaft domain is a structural counterpart to the adenovirus spike shaft. The structural relationships between PRD1, TNF, and adenovirus proteins suggest that the vertex proteins may have originated from an ancestral TNF-like jelly roll coat protein via a combination of gene duplication and deletion.

Spike sorting based upon machine learning algorithms (SOMA).

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Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

Upscaling the impact of convective overshooting (COV) through BRAMS: a continental and wet-season scale study of the water vapour (WV) budget in the tropical tropopause layer (TTL).

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Behera, Abhinna; Rivière, Emmanuel; Marécal, Virginie; Rysman, Jean-François; Claud, Chantal; Burgalat, Jérémie

2017-04-01

The stratospheric water vapour (WV) has a conceding impact on the radiative and chemical budget of Earth's atmosphere. The convective overshooting (COV) at the tropics is well admitted for playing a role in transporting directly WV to the stratosphere. Nonetheless, its impact on the lower stratosphere is yet to be determined at global scale, as the satellite and other air-borne measurements are not of having fine enough resolution to quantify this impact at large scale. Therefore, efforts have been made to quantify the influence of COV over the WV budget in the tropical tropopause layer (TTL) through modelling. Our approach is to build two synthetic tropical wet-seasons; where one would be having only deep convection (DC) but no COV at all, and the second one would be having the COV, and in both cases the WV budget in the TTL would be estimated. Before that, a French-Brazilian TRO-pico campaign was carried out at Bauru, Brazil in order to understand the influence of COV on the WV budget in the TTL. The radio-sounding, and the small balloon-borne WV measurements from the campaign are being utilized to validate the model simulation. Brazilian version of Regional Atmospheric Modeling System (BRAMS) is used with a single grid system to simulate a WV variability in a wet-season. Grell's convective parameterization with ensemble closure, microphysics with double moment scheme and 7 types of hydrometeors are incorporated to simulate the WV variability for a wet-season at the tropics. The grid size of simulation is chosen to be 20 km x 20 km horizontally and from surface to 30 km altitude, so that there cannot be COV at all, only DC due to such a relatively coarse resolution. The European Centre for Medium-range Weather Forecasts (ECMWF) operational analyses data are used every 6 hours for grid initialization and boundary conditions, and grid center nudging. The simulation is carried out for a full wet-season (Nov 2012 - Mar 2013) at Brazilian scale, so that it would

Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

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Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

2017-10-01

Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

Ship Classification with High Resolution TerraSAR-X Imagery Based on Analytic Hierarchy Process

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Zhi Zhao

2013-01-01

Full Text Available Ship surveillance using space-borne synthetic aperture radar (SAR, taking advantages of high resolution over wide swaths and all-weather working capability, has attracted worldwide attention. Recent activity in this field has concentrated mainly on the study of ship detection, but the classification is largely still open. In this paper, we propose a novel ship classification scheme based on analytic hierarchy process (AHP in order to achieve better performance. The main idea is to apply AHP on both feature selection and classification decision. On one hand, the AHP based feature selection constructs a selection decision problem based on several feature evaluation measures (e.g., discriminability, stability, and information measure and provides objective criteria to make comprehensive decisions for their combinations quantitatively. On the other hand, we take the selected feature sets as the input of KNN classifiers and fuse the multiple classification results based on AHP, in which the feature sets’ confidence is taken into account when the AHP based classification decision is made. We analyze the proposed classification scheme and demonstrate its results on a ship dataset that comes from TerraSAR-X SAR images.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

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Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Comparison of two next-generation sequencing kits for diagnosis of epileptic disorders with a user-friendly tool for displaying gene coverage, DeCovA

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Sarra Dimassi

2015-12-01

Full Text Available In recent years, molecular genetics has been playing an increasing role in the diagnostic process of monogenic epilepsies. Knowing the genetic basis of one patient's epilepsy provides accurate genetic counseling and may guide therapeutic options. Genetic diagnosis of epilepsy syndromes has long been based on Sanger sequencing and search for large rearrangements using MLPA or DNA arrays (array-CGH or SNP-array. Recently, next-generation sequencing (NGS was demonstrated to be a powerful approach to overcome the wide clinical and genetic heterogeneity of epileptic disorders. Coverage is critical for assessing the quality and accuracy of results from NGS. However, it is often a difficult parameter to display in practice. The aim of the study was to compare two library-building methods (Haloplex, Agilent and SeqCap EZ, Roche for a targeted panel of 41 genes causing monogenic epileptic disorders. We included 24 patients, 20 of whom had known disease-causing mutations. For each patient both libraries were built in parallel and sequenced on an Ion Torrent Personal Genome Machine (PGM. To compare coverage and depth, we developed a simple homemade tool, named DeCovA (Depth and Coverage Analysis. DeCovA displays the sequencing depth of each base and the coverage of target genes for each genomic position. The fraction of each gene covered at different thresholds could be easily estimated. None of the two methods used, namely NextGene and Ion Reporter, were able to identify all the known mutations/CNVs displayed by the 20 patients. Variant detection rate was globally similar for the two techniques and DeCovA showed that failure to detect a mutation was mainly related to insufficient coverage.

Combining TerraSAR-X and SPOT-5 data for object-based landslide detection

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Friedl, B.; Hölbling, D.; Füreder, P.

2012-04-01

Landslide detection and classification is an essential requirement in pre- and post-disaster hazard analysis. In earlier studies landslide detection often was achieved through time-consuming and cost-intensive field surveys and visual orthophoto interpretation. Recent studies show that Earth Observation (EO) data offer new opportunities for fast, reliable and accurate landslide detection and classification, which may conduce to an effective landslide monitoring and landslide hazard management. To ensure the fast recognition and classification of landslides at a regional scale, a (semi-)automated object-based landslide detection approach is established for a study site situated in the Huaguoshan catchment, Southern Taiwan. The study site exhibits a high vulnerability to landslides and debris flows, which are predominantly typhoon-induced. Through the integration of optical satellite data (SPOT-5 with 2.5 m GSD), SAR (Synthetic Aperture Radar) data (TerraSAR-X Spotlight with 2.95 m GSD) and digital elevation information (DEM with 5 m GSD) including its derived products (e.g. slope, curvature, flow accumulation) landslides may be examined in a more efficient way as if relying on single data sources only. The combination of optical and SAR data in an object-based image analysis (OBIA) domain for landslide detection and classification has not been investigated so far, even if SAR imagery show valuable properties for landslide detection, which differ from optical data (e.g. high sensitivity to surface roughness and soil moisture). The main purpose of this study is to recognize and analyze existing landslides by applying object-based image analysis making use of eCognition software. OBIA provides a framework for examining features defined by spectral, spatial, textural, contextual as well as hierarchical properties. Objects are derived through image segmentation and serve as input for the classification process, which relies on transparent rulesets, representing knowledge

Performance evaluation of PCA-based spike sorting algorithms.

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Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George

2008-09-01

Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts.

Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering.

Science.gov (United States)

Chah, E; Hok, V; Della-Chiesa, A; Miller, J J H; O'Mara, S M; Reilly, R B

2011-02-01

This study presents a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means clustering. The performance of the proposed method was compared against previously reported algorithms such as principal component analysis (PCA) and amplitude-based feature extraction. Two types of classifier (namely k-means and classification expectation-maximization) were incorporated within the spike sorting algorithms, in order to find a suitable classifier for the feature sets. Simulated data sets and in-vivo tetrode multichannel recordings were employed to assess the performance of the spike sorting algorithms. The results show that the proposed algorithm yields significantly improved performance with mean sorting accuracy of 73% and sorting error of 10% compared to PCA which combined with k-means had a sorting accuracy of 58% and sorting error of 10%.A correction was made to this article on 22 February 2011. The spacing of the title was amended on the abstract page. No changes were made to the article PDF and the print version was unaffected.

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

Science.gov (United States)

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search

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Yuan-Jyun Chang

2016-12-01

Full Text Available The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO. The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

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Simon Plank

2016-04-01

Full Text Available Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth’s landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

Method of Monitoring Urban Area Deformation Based on Differential TomoSAR

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WANG Aichun

2016-12-01

Full Text Available While the use of differential TomoSAR based on compressive sensing (CS makes it possible to solve the layover problem and reconstruct the deformation information of an observed urban area scene acquired by moderate-high resolution SAR satellite, the performance of the reconstruction decreases for a sparse and structural observed scene due to ignoring the structural characteristics of the observed scene. To deal with this issue, the method for differential SAR tomography based on Khatri-Rao subspace and block compressive sensing (KRS-BCS is proposed. The proposed method changes the reconstruction of the sparse and structural observed scene into a BCS problem under Khatri-Rao subspace, using the structure information of the observed scene and Khatri-Rao product property of the reconstructed observation matrix for differential TomoSAR, such that the KRS-BCS problem is efficiently solved with a block sparse l1/l2 norm optimization signal model, and the performance of resolution capability and reconstruction estimation is compared and analyzed qualitatively and quantitatively by the theoretical analysis and the simulation experiments, all of the results show the propose KRS-BCS method practicably overcomes the problems of CS method, as well as, quite maintains the high resolution characteristics, effectively reduces the probability of false scattering target and greatly improves the reconstruction accurate of scattering point. Finally, the application is taking the urban area of the Mobara(in Chiba, Japan as the test area and using 34 ENVISAT-ASAR images, the accuracy is verifying with the reference deformations derived from first level point data and GPS tracking data, the results show the trend is consistent and the overall deviation is small between reconstruction deformations of the propose KRS-BCS method and the reference deformations, and the accuracy is high in the estimation of the urban area deformation.

Spike-timing-based computation in sound localization.

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Dan F M Goodman

2010-11-01

Full Text Available Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

Science.gov (United States)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

Science.gov (United States)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

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Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

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R. Dwivedi

2016-06-01

Full Text Available In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS and Small Baseline (SB methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS based PS-InSAR and the Small Baselines Subset (SBAS techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

Self-control with spiking and non-spiking neural networks playing games.

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Christodoulou, Chris; Banfield, Gaye; Cleanthous, Aristodemos

2010-01-01

Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that they have self-control problems and attempt to overcome them by applying precommitment. Problems in exercising self-control, suggest a conflict between cognition and motivation, which has been linked to competition between higher and lower brain functions (representing the frontal lobes and the limbic system respectively). This premise of an internal process conflict, lead to a behavioural model being proposed, based on which, we implemented a computational model for studying and explaining self-control through precommitment behaviour. Our model consists of two neural networks, initially non-spiking and then spiking ones, representing the higher and lower brain systems viewed as cooperating for the benefit of the organism. The non-spiking neural networks are of simple feed forward multilayer type with reinforcement learning, one with selective bootstrap weight update rule, which is seen as myopic, representing the lower brain and the other with the temporal difference weight update rule, which is seen as far-sighted, representing the higher brain. The spiking neural networks are implemented with leaky integrate-and-fire neurons with learning based on stochastic synaptic transmission. The differentiating element between the two brain centres in this implementation is based on the memory of past actions determined by an eligibility trace time constant. As the structure of the self-control problem can be likened to the Iterated Prisoner's Dilemma (IPD) game in that cooperation is to defection what self-control is to impulsiveness or what compromising is to insisting, we implemented the neural networks as two players, learning simultaneously but independently, competing in the IPD game. With a technique resembling the precommitment effect, whereby the

SARS-related Perceptions in Hong Kong

OpenAIRE

Lau, Joseph T.F.; Yang, Xilin; Pang, Ellie; Tsui, H.Y.; Wong, Eric; Wing, Yun Kwok

2005-01-01

To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means o...

SARS-related perceptions in Hong Kong.

Science.gov (United States)

Lau, Joseph T F; Yang, Xilin; Pang, Ellie; Tsui, H Y; Wong, Eric; Wing, Yun Kwok

2005-03-01

To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means of prevention; 40.4% believed that SARS would resurge in Hong Kong; and approximately equals 70% would then wear masks in public places. High percentages of respondents felt helpless, horrified, and apprehensive because of SARS. Approximately 16% showed signs of posttraumatic symptoms, and approximately equals 40% perceived increased stress in family or work settings. The general public in Hong Kong has been very vigilant about SARS but needs to be more psychologically prepared to face a resurgence of the epidemic.

Object Georeferencing in UAV-Based SAR Terrain Images

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Łabowski Michał

2016-12-01

Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

The generation of simple compliance boundaries for mobile communication base station antennas using formulae for SAR estimation.

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Thors, B; Hansson, B; Törnevik, C

2009-07-07

In this paper, a procedure is proposed for generating simple and practical compliance boundaries for mobile communication base station antennas. The procedure is based on a set of formulae for estimating the specific absorption rate (SAR) in certain directions around a class of common base station antennas. The formulae, given for both whole-body and localized SAR, require as input the frequency, the transmitted power and knowledge of antenna-related parameters such as dimensions, directivity and half-power beamwidths. With knowledge of the SAR in three key directions it is demonstrated how simple and practical compliance boundaries can be generated outside of which the exposure levels do not exceed certain limit values. The conservativeness of the proposed procedure is discussed based on results from numerical radio frequency (RF) exposure simulations with human body phantoms from the recently developed Virtual Family.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

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Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks

SAR Raw Data Generation for Complex Airport Scenes

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Jia Li

2014-10-01

Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

p53 down-regulates SARS coronavirus replication and is targeted by the SARS-unique domain and PLpro via E3 ubiquitin ligase RCHY1

Science.gov (United States)

Ma-Lauer, Yue; Carbajo-Lozoya, Javier; Müller, Marcel A.; Deng, Wen; Lei, Jian; Meyer, Benjamin; Kusov, Yuri; von Brunn, Brigitte; Bairad, Dev Raj; Hünten, Sabine; Drosten, Christian; Hermeking, Heiko; Leonhardt, Heinrich; Mann, Matthias; Hilgenfeld, Rolf; von Brunn, Albrecht

2016-01-01

Highly pathogenic severe acute respiratory syndrome coronavirus (SARS-CoV) has developed strategies to inhibit host immune recognition. We identify cellular E3 ubiquitin ligase ring-finger and CHY zinc-finger domain-containing 1 (RCHY1) as an interacting partner of the viral SARS-unique domain (SUD) and papain-like protease (PLpro), and, as a consequence, the involvement of cellular p53 as antagonist of coronaviral replication. Residues 95–144 of RCHY1 and 389–652 of SUD (SUD-NM) subdomains are crucial for interaction. Association with SUD increases the stability of RCHY1 and augments RCHY1-mediated ubiquitination as well as degradation of p53. The calcium/calmodulin-dependent protein kinase II delta (CAMK2D), which normally influences RCHY1 stability by phosphorylation, also binds to SUD. In vivo phosphorylation shows that SUD does not regulate phosphorylation of RCHY1 via CAMK2D. Similarly to SUD, the PLpros from SARS-CoV, MERS-CoV, and HCoV-NL63 physically interact with and stabilize RCHY1, and thus trigger degradation of endogenous p53. The SARS-CoV papain-like protease is encoded next to SUD within nonstructural protein 3. A SUD–PLpro fusion interacts with RCHY1 more intensively and causes stronger p53 degradation than SARS-CoV PLpro alone. We show that p53 inhibits replication of infectious SARS-CoV as well as of replicons and human coronavirus NL63. Hence, human coronaviruses antagonize the viral inhibitor p53 via stabilizing RCHY1 and promoting RCHY1-mediated p53 degradation. SUD functions as an enhancer to strengthen interaction between RCHY1 and nonstructural protein 3, leading to a further increase in in p53 degradation. The significance of these findings is that down-regulation of p53 as a major player in antiviral innate immunity provides a long-sought explanation for delayed activities of respective genes. PMID:27519799

Tracking morphological changes and slope instability using spaceborne and ground-based SAR data

Science.gov (United States)

Di Traglia, Federico; Nolesini, Teresa; Ciampalini, Andrea; Solari, Lorenzo; Frodella, William; Bellotti, Fernando; Fumagalli, Alfio; De Rosa, Giuseppe; Casagli, Nicola

2018-01-01

Stromboli (Aeolian Archipelago, Italy) is an active volcano that is frequently affected by moderate to large mass wasting, which has occasionally triggered tsunamis. With the aim of understanding the relationship between the geomorphologic evolution and slope instability of Stromboli, remote sensing information from space-born Synthetic Aperture Radar (SAR) change detection and interferometry (InSAR) () and Ground Based InSAR (GBInSAR) was compared with field observations and morphological analyses. Ground reflectivity and SqueeSAR™ (an InSAR algorithm for surface deformation monitoring) displacement measurements from X-band COSMO-SkyMed satellites (CSK) were analysed together with displacement measurements from a permanent-sited, Ku-band GBInSAR system. Remote sensing results were compared with a preliminary morphological analysis of the Sciara del Fuoco (SdF) steep volcanic flank, which was carried out using a high-resolution Digital Elevation Model (DEM). Finally, field observations, supported by infrared thermographic surveys (IRT), allowed the interpretation and validation of remote sensing data. The analysis of the entire dataset (collected between January 2010 and December 2014) covers a period characterized by a low intensity of Strombolian activity. This period was punctuated by the occurrence of lava overflows, occurring from the crater terrace evolving downslope toward SdF, and flank eruptions, such as the 2014 event. The amplitude of the CSK images collected between February 22nd, 2010, and December 18th, 2014, highlights that during periods characterized by low-intensity Strombolian activity, the production of materials ejected from the crater terrace towards the SdF is generally low, and erosion is the prevailing process mainly affecting the central sector of the SdF. CSK-SqueeSAR™ and GBInSAR data allowed the identification of low displacements in the SdF, except for high displacement rates (up to 1.5 mm/h) that were measured following both lava

Spiking neural network for recognizing spatiotemporal sequences of spikes

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2004-01-01

Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

Inhibition of severe acute respiratory syndrome coronavirus replication in a lethal SARS-CoV BALB/c mouse model by stinging nettle lectin, Urtica dioica agglutinin

Science.gov (United States)

Kumaki, Yohichi; Wandersee, Miles K.; Smith, Aaron J.; Zhou, Yanchen; Simmons, Graham; Nelson, Nathan M.; Bailey, Kevin W.; Vest, Zachary G.; Li, Joseph K.-K.; Chan, Paul Kay-Sheung; Smee, Donald F.; Barnard, Dale L.

2011-01-01

Urtica dioica agglutinin (UDA) is a small plant monomeric lectin, 8.7 kDa in size, with an N-acetylglucosamine specificity that inhibits viruses from Nidovirales in vitro. In the current study, we first examined the efficacy of UDA on the replication of different SARS-CoV strains in Vero 76 cells. UDA inhibited virus replication in a dose-dependent manner and reduced virus yields of the Urbani strain by 90% at 1.1 ± 0.4 µg/ml in Vero 76 cells. Then, UDA was tested for efficacy in a lethal SARS-CoV-infected BALB/c mouse model. BALB/c mice were infected with two LD50 (575 PFU) of virus for 4 hours before the mice were treated intraperitoneally with UDA at 20, 10, 5 or 0 mg/kg/day for 4 days. Treatment with UDA at 5 mg/kg significantly protected the mice against a lethal infection with mouse-adapted SARS-CoV (p<0.001), but did not significantly reduce virus lung titers. All virus-infected mice receiving UDA treatments were also significantly protected against weight loss (p<0.001). UDA also effectively reduced lung pathology scores. At day 6 after virus exposure, all groups of mice receiving UDA had much lower lung weights than did the placebo-treated mice. Thus, our data suggest that UDA treatment of SARS infection in mice leads to a substantial therapeutic effect that protects mice against death and weight loss. Furthermore, the mode of action of UDA in vitro was further investigated using live SARS-CoV Urbani strain virus and retroviral particles pseudotyped with SARS-CoV spike (S). UDA specifically inhibited the replication of live SARS-CoV or SARS-CoV pseudotyped virus when added just before, but not after, adsorption. These data suggested that UDA likely inhibits SARS-CoV infection by targeting early stages of the replication cycle, namely, adsorption or penetration. In addition, we demonstrated that UDA neutralizes the virus infectivity, presumably by binding to the SARS-CoV spike (S) glycoprotein. Finally, the target molecule for inhibition of virus

Improved SpikeProp for Using Particle Swarm Optimization

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Falah Y. H. Ahmed

2013-01-01

Full Text Available A spiking neurons network encodes information in the timing of individual spike times. A novel supervised learning rule for SpikeProp is derived to overcome the discontinuities introduced by the spiking thresholding. This algorithm is based on an error-backpropagation learning rule suited for supervised learning of spiking neurons that use exact spike time coding. The SpikeProp is able to demonstrate the spiking neurons that can perform complex nonlinear classification in fast temporal coding. This study proposes enhancements of SpikeProp learning algorithm for supervised training of spiking networks which can deal with complex patterns. The proposed methods include the SpikeProp particle swarm optimization (PSO and angle driven dependency learning rate. These methods are presented to SpikeProp network for multilayer learning enhancement and weights optimization. Input and output patterns are encoded as spike trains of precisely timed spikes, and the network learns to transform the input trains into target output trains. With these enhancements, our proposed methods outperformed other conventional neural network architectures.

Deep learning for SAR image formation

Science.gov (United States)

Mason, Eric; Yonel, Bariscan; Yazici, Birsen

2017-04-01

The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

Science.gov (United States)

Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

2017-12-01

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

Simple networks for spike-timing-based computation, with application to olfactory processing.

Science.gov (United States)

Brody, Carlos D; Hopfield, J J

2003-03-06

Spike synchronization across neurons can be selective for the situation where neurons are driven at similar firing rates, a "many are equal" computation. This can be achieved in the absence of synaptic interactions between neurons, through phase locking to a common underlying oscillatory potential. Based on this principle, we instantiate an algorithm for robust odor recognition into a model network of spiking neurons whose main features are taken from known properties of biological olfactory systems. Here, recognition of odors is signaled by spike synchronization of specific subsets of "mitral cells." This synchronization is highly odor selective and invariant to a wide range of odor concentrations. It is also robust to the presence of strong distractor odors, thus allowing odor segmentation within complex olfactory scenes. Information about odors is encoded in both the identity of glomeruli activated above threshold (1 bit of information per glomerulus) and in the analog degree of activation of the glomeruli (approximately 3 bits per glomerulus).

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

DEFF Research Database (Denmark)

Tully, Philip J; Lindén, Henrik; Hennig, Matthias H

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed...... in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods...

Acetylene Black Induced Heterogeneous Growth of Macroporous CoV2O6 Nanosheet for High-Rate Pseudocapacitive Lithium-Ion Battery Anode.

Science.gov (United States)

Zhang, Lei; Zhao, Kangning; Luo, Yanzhu; Dong, Yifan; Xu, Wangwang; Yan, Mengyu; Ren, Wenhao; Zhou, Liang; Qu, Longbing; Mai, Liqiang

2016-03-23

Metal vanadates suffer from fast capacity fading in lithium-ion batteries especially at a high rate. Pseudocapacitance, which is associated with surface or near-surface redox reactions, can provide fast charge/discharge capacity free from diffusion-controlled intercalation processes and is able to address the above issue. In this work, we report the synthesis of macroporous CoV2O6 nanosheets through a facile one-pot method via acetylene black induced heterogeneous growth. When applied as lithium-ion battery anode, the macroporous CoV2O6 nanosheets show typical features of pseudocapacitive behavior: (1) currents that are mostly linearly dependent on sweep rate and (2) redox peaks whose potentials do not shift significantly with sweep rate. The macroporous CoV2O6 nanosheets display a high reversible capacity of 702 mAh g(-1) at 200 mA g(-1), excellent cyclability with a capacity retention of 89% (against the second cycle) after 500 cycles at 500 mA g(-1), and high rate capability of 453 mAh g(-1) at 5000 mA g(-1). We believe that the introduction of pseudocapacitive properties in lithium battery is a promising direction for developing electrode materials with high-rate capability.

Analysis of the equalizing holes resistance in fuel assembly spike for lead-based reactor

International Nuclear Information System (INIS)

Zhang, Guangyu; Jin, Ming; Wang, Jianye; Song, Yong

2017-01-01

Highlights: • A RELAP5 model for a 10 MWth lead-based reactor was built to study the hydrodynamic characteristics between the equalizing holes in the fuel assembly spike. • Different fuel assembly total blockage scenarios and different resistances for different fuel assemblies were examined. • The inherent safety characteristics of the lead-based reactor was improved by optimizing the configuration of equalizing holes in the fuel assembly spike. - Abstract: To avoid the damage of the fuel rod cladding when a fuel assembly (FA) is totally blocked, a special configuration of the fuel assembly spike was designed with some equalizing holes in the center region which can let the coolant to flow during the totally blockage scenarios of FA. To study the hydrodynamic characteristics between the equalizing holes and an appropriate resistance, a RELAP5 model was developed for a 10 MWth lead-based reactor which used lead-bismuth as coolant. Several FA total blockage and partial core blockage scenarios were selected. The simulation results indicated that when all the FA spike equalizing holes had the same hydraulic resistance, only a narrow range of suitable equalizing holes resistances could be chosen when a FA was blocked. However, in the two or more FA blockage scenarios, there were no appropriate resistances to meet the requirement. In addition, with different FA spike equalizing holes with different resistances, a large range of suitable equalizing hole resistances could be chosen. Especially a series of suitable resistances were selected when the small power FA resistance was 1/2, 1/4, 1/8 of the large one. Under these circumstances, one, two or three FA blockages would not damage the core. These demonstrated that selecting a series of suitable hydraulic resistances for the equalizing holes could improve the safety characteristics of the reactor effectively.

Attribute Learning for SAR Image Classification

Directory of Open Access Journals (Sweden)

Chu He

2017-04-01

Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

iSpike: a spiking neural interface for the iCub robot

International Nuclear Information System (INIS)

Gamez, D; Fidjeland, A K; Lazdins, E

2012-01-01

This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot’s sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL. (paper)

Infrastructure monitoring with spaceborne SAR sensors

CERN Document Server

ANGHEL, ANDREI; CACOVEANU, REMUS

2017-01-01

This book presents a novel non-intrusive infrastructure monitoring technique based on the detection and tracking of scattering centers in spaceborne SAR images. The methodology essentially consists of refocusing each available SAR image on an imposed 3D point cloud associated to the envisaged infrastructure element and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The methodology described in this book provides a new perspective on infrastructure monitoring with spaceborne SAR images, is based on a standalone processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and researchers working in the area of critical infrastructure monitoring by radar remote sensing.

An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

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Xiangguang Leng

2016-08-01

Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

Kinetic Modeling of Methionine Oxidation in Monoclonal Antibodies from Hydrogen Peroxide Spiking Studies.

Science.gov (United States)

Hui, Ada; Lam, Xanthe M; Kuehl, Christopher; Grauschopf, Ulla; Wang, Y John

2015-01-01

When isolator technology is applied to biotechnology drug product fill-finish process, hydrogen peroxide (H2O2) spiking studies for the determination of the sensitivity of protein to residual peroxide in the isolator can be useful for assessing a maximum vapor phase hydrogen peroxide (VPHP) level. When monoclonal antibody (mAb) drug products were spiked with H2O2, an increase in methionine (Met 252 and Met 428) oxidation in the Fc region of the mAbs with a decrease in H2O2 concentration was observed for various levels of spiked-in peroxide. The reaction between Fc-Met and H2O2 was stoichiometric (i.e., 1:1 molar ratio), and the reaction rate was dependent on the concentrations of mAb and H2O2. The consumption of H2O2 by Fc-Met oxidation in the mAb followed pseudo first-order kinetics, and the rate was proportional to mAb concentration. The extent of Met 428 oxidation was half of that of Met 252, supporting that Met 252 is twice as reactive as Met 428. Similar results were observed for free L-methionine when spiked with H2O2. However, mAb formulation excipients may affect the rate of H2O2 consumption. mAb formulations containing trehalose or sucrose had faster H2O2 consumption rates than formulations without the sugars, which could be the result of impurities (e.g., metal ions) present in the excipients that may act as catalysts. Based on the H2O2 spiking study results, we can predict the amount Fc-Met oxidation for a given protein concentration and H2O2 level. Our kinetic modeling of the reaction between Fc-Met oxidation and H2O2 provides an outline to design a H2O2 spiking study to support the use of VPHP isolator for antibody drug product manufacture. Isolator technology is increasing used in drug product manufacturing of biotherapeutics. In order to understand the impact of residual vapor phase hydrogen peroxide (VPHP) levels on protein product quality, hydrogen peroxide (H2O2) spiking studies may be performed to determine the sensitivity of monoclonal antibody

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

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Xiangwei Xing

2014-01-01

Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Feature extraction for SAR target recognition based on supervised manifold learning

International Nuclear Information System (INIS)

Du, C; Zhou, S; Sun, J; Zhao, J

2014-01-01

On the basis of manifold learning theory, a new feature extraction method for Synthetic aperture radar (SAR) target recognition is proposed. First, the proposed algorithm estimates the within-class and between-class local neighbourhood surrounding each SAR sample. After computing the local tangent space for each neighbourhood, the proposed algorithm seeks for the optimal projecting matrix by preserving the local within-class property and simultaneously maximizing the local between-class separability. The use of uncorrelated constraint can also enhance the discriminating power of the optimal projecting matrix. Finally, the nearest neighbour classifier is applied to recognize SAR targets in the projected feature subspace. Experimental results on MSTAR datasets demonstrate that the proposed method can provide a higher recognition rate than traditional feature extraction algorithms in SAR target recognition

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

Science.gov (United States)

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Modelling of potentially promising SARS protease inhibitors

International Nuclear Information System (INIS)

Plewczynski, Dariusz; Hoffmann, Marcin; Grotthuss, Marcin von; Knizewski, Lukasz; Rychewski, Leszek; Eitner, Krystian; Ginalski, Krzysztof

2007-01-01

In many cases, at the beginning of a high throughput screening experiment some information about active molecules is already available. Active compounds (such as substrate analogues, natural products and inhibitors of related proteins) are often identified in low throughput validation studies on a biochemical target. Sometimes the additional structural information is also available from crystallographic studies on protein and ligand complexes. In addition, the structural or sequence similarity of various protein targets yields a novel possibility for drug discovery. Co-crystallized compounds from homologous proteins can be used to design leads for a new target without co-crystallized ligands. In this paper we evaluate how far such an approach can be used in a real drug campaign, with severe acute respiratory syndrome (SARS) coronavirus providing an example. Our method is able to construct small molecules as plausible inhibitors solely on the basis of the set of ligands from crystallized complexes of a protein target, and other proteins from its structurally homologous family. The accuracy and sensitivity of the method are estimated here by the subsequent use of an electronic high throughput screening flexible docking algorithm. The best performing ligands are then used for a very restrictive similarity search for potential inhibitors of the SARS protease within the million compounds from the Ligand.Info small molecule meta-database. The selected molecules can be passed on for further experimental validation

Modelling of potentially promising SARS protease inhibitors

Energy Technology Data Exchange (ETDEWEB)

Plewczynski, Dariusz [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland); Hoffmann, Marcin [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Grotthuss, Marcin von [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Knizewski, Lukasz [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland); Rychewski, Leszek [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Eitner, Krystian [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Ginalski, Krzysztof [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland)

2007-07-18

In many cases, at the beginning of a high throughput screening experiment some information about active molecules is already available. Active compounds (such as substrate analogues, natural products and inhibitors of related proteins) are often identified in low throughput validation studies on a biochemical target. Sometimes the additional structural information is also available from crystallographic studies on protein and ligand complexes. In addition, the structural or sequence similarity of various protein targets yields a novel possibility for drug discovery. Co-crystallized compounds from homologous proteins can be used to design leads for a new target without co-crystallized ligands. In this paper we evaluate how far such an approach can be used in a real drug campaign, with severe acute respiratory syndrome (SARS) coronavirus providing an example. Our method is able to construct small molecules as plausible inhibitors solely on the basis of the set of ligands from crystallized complexes of a protein target, and other proteins from its structurally homologous family. The accuracy and sensitivity of the method are estimated here by the subsequent use of an electronic high throughput screening flexible docking algorithm. The best performing ligands are then used for a very restrictive similarity search for potential inhibitors of the SARS protease within the million compounds from the Ligand.Info small molecule meta-database. The selected molecules can be passed on for further experimental validation.

Wavelet analysis of epileptic spikes

Science.gov (United States)

Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Wavelet analysis of epileptic spikes

CERN Document Server

Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-01-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

SAR image classification based on CNN in real and simulation datasets

Science.gov (United States)

Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-04-01

Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

TerraSAR-X InSAR multipass analysis on Venice, Italy)

Science.gov (United States)

Nitti, D. O.; Nutricato, R.; Bovenga, F.; Refice, A.; Chiaradia, M. T.; Guerriero, L.

2009-09-01

The TerraSAR-X (copyright) mission, launched in 2007, carries a new X-band Synthetic Aperture Radar (SAR) sensor optimally suited for SAR interferometry (InSAR), thus allowing very promising application of InSAR techniques for the risk assessment on areas with hydrogeological instability and especially for multi-temporal analysis, such as Persistent Scatterer Interferometry (PSI) techniques, originally developed at Politecnico di Milano. The SPINUA (Stable Point INterferometry over Unurbanised Areas) technique is a PSI processing methodology which has originally been developed with the aim of detection and monitoring of coherent PS targets in non or scarcely-urbanized areas. The main goal of the present work is to describe successful applications of the SPINUA PSI technique in processing X-band data. Venice has been selected as test site since it is in favorable settings for PSI investigations (urban area containing many potential coherent targets such as buildings) and in view of the availability of a long temporal series of TerraSAR-X stripmap acquisitions (27 scenes in all). The Venice Lagoon is affected by land sinking phenomena, whose origins are both natural and man-induced. The subsidence of Venice has been intensively studied for decades by determining land displacements through traditional monitoring techniques (leveling and GPS) and, recently, by processing stacks of ERS/ENVISAT SAR data. The present work is focused on an independent assessment of application of PSI techniques to TerraSAR-X stripmap data for monitoring the stability of the Venice area. Thanks to its orbital repeat cycle of only 11 days, less than a third of ERS/ENVISAT C-band missions, the maximum displacement rate that can be unambiguously detected along the Line-of-Sight (LOS) with TerraSAR-X SAR data through PSI techniques is expected to be about twice the corresponding value of ESA C-band missions, being directly proportional to the sensor wavelength and inversely proportional to the

Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site

Directory of Open Access Journals (Sweden)

Federica Bardi

2016-03-01

Full Text Available This work concerns a proposal of the integration of InSAR (Interferometric Synthetic Aperture Radar data acquired by ground-based (GB and satellite platforms. The selected test site is the Åknes rockslide, which affects the western Norwegian coast. The availability of GB-InSAR and satellite InSAR data and the accessibility of a wide literature make the landslide suitable for testing the proposed procedure. The first step consists of the organization of a geodatabase, performed in the GIS environment, containing all of the available data. The second step concerns the analysis of satellite and GB-InSAR data, separately. Two datasets, acquired by RADARSAT-2 (related to a period between October 2008 and August 2013 and by a combination of TerraSAR-X and TanDEM-X (acquired between July 2010 and October 2012, both of them in ascending orbit, processed applying SBAS (Small BAseline Subset method, are available. GB-InSAR data related to five different campaigns of measurements, referred to the summer seasons of 2006, 2008, 2009, 2010 and 2012, are available, as well. The third step relies on data integration, performed firstly from a qualitative point of view and later from a semi-quantitative point of view. The results of the proposed procedure have been validated by comparing them to GPS (Global Positioning System data. The proposed procedure allowed us to better define landslide sectors in terms of different ranges of displacements. From a qualitative point of view, stable and unstable areas have been distinguished. In the sector concerning movement, two different sectors have been defined thanks to the results of the semi-quantitative integration step: the first sector, concerning displacement values higher than 10 mm, and the 2nd sector, where the displacements did not exceed a 10-mm value of displacement in the analyzed period.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

Directory of Open Access Journals (Sweden)

Philip J Tully

2016-05-01

Full Text Available Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx. We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

Origin, diversity and maturation of human antiviral antibodies analyzed by high-throughput sequencing

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Ponraj ePrabakaran

2012-08-01

Full Text Available Our understanding of how antibodies are generated and function could help develop effective vaccines and antibody-based therapeutics against viruses such as HIV-1, SARS Coronavirus (CoV, and Hendra and Nipah viruses (henipaviruses. Although broadly neutralizing antibodies (bnAbs against the HIV-1 were observed in patients, elicitation of such bnAbs remains a major challenge when compared to other viral targets. We previously hypothesized that HIV-1 could have evolved a strategy to evade the immune system due to absent or very weak binding of germline antibodies to the conserved epitopes that may not be sufficient to initiate and/or maintain an effective immune response. To further explore our hypothesis, we used the 454 sequence analysis of a large naïve library of human IgM antibodies which had been used for selecting antibodies against SARS Coronavirus (CoV receptor-binding domain (RBD, and soluble G proteins (sG of Hendra and Nipah viruses (henipaviruses. We found that the human IgM repertoires from the 454 sequencing have diverse germline usages, recombination patterns, junction diversity and a lower extent of somatic mutation. In this study, we identified germline intermediates of antibodies specific to HIV-1 and other viruses as observed in normal individuals, and compared their genetic diversity and somatic mutation level along with available structural and functional data. Further computational analysis will provide framework for understanding the underlying genetic and molecular determinants related to maturation pathways of antiviral bnAbs that could be useful for applying novel approaches to the design of effective vaccine immunogens and antibody-based therapeutics.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

Science.gov (United States)

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

Science.gov (United States)

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods

Directory of Open Access Journals (Sweden)

Claire Ramus

2016-03-01

Full Text Available This data article describes a controlled, spiked proteomic dataset for which the “ground truth” of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier http://www.ebi.ac.uk/pride/archive/projects/PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values.

Causal Inference and Explaining Away in a Spiking Network

Science.gov (United States)

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Inhibition of severe acute respiratory syndrome coronavirus replication in a lethal SARS-CoV BALB/c mouse model by stinging nettle lectin, Urtica dioica agglutinin.

Science.gov (United States)

Kumaki, Yohichi; Wandersee, Miles K; Smith, Aaron J; Zhou, Yanchen; Simmons, Graham; Nelson, Nathan M; Bailey, Kevin W; Vest, Zachary G; Li, Joseph K-K; Chan, Paul Kay-Sheung; Smee, Donald F; Barnard, Dale L

2011-04-01

Urtica dioica agglutinin (UDA) is a small plant monomeric lectin, 8.7 kDa in size, with an N-acetylglucosamine specificity that inhibits viruses from Nidovirales in vitro. In the current study, we first examined the efficacy of UDA on the replication of different SARS-CoV strains in Vero 76 cells. UDA inhibited virus replication in a dose-dependent manner and reduced virus yields of the Urbani strain by 90% at 1.1 ± 0.4 μg/ml in Vero 76 cells. Then, UDA was tested for efficacy in a lethal SARS-CoV-infected BALB/c mouse model. BALB/c mice were infected with two LD50 (575 PFU) of virus for 4 h before the mice were treated intraperitoneally with UDA at 20, 10, 5 or 0 mg/kg/day for 4 days. Treatment with UDA at 5 mg/kg significantly protected the mice against a lethal infection with mouse-adapted SARS-CoV (p < 0.001), but did not significantly reduce virus lung titers. All virus-infected mice receiving UDA treatments were also significantly protected against weight loss (p < 0.001). UDA also effectively reduced lung pathology scores. At day 6 after virus exposure, all groups of mice receiving UDA had much lower lung weights than did the placebo-treated mice. Thus, our data suggest that UDA treatment of SARS infection in mice leads to a substantial therapeutic effect that protects mice against death and weight loss. Furthermore, the mode of action of UDA in vitro was further investigated using live SARS-CoV Urbani strain virus and retroviral particles pseudotyped with SARS-CoV spike (S). UDA specifically inhibited the replication of live SARS-CoV or SARS-CoV pseudotyped virus when added just before, but not after, adsorption. These data suggested that UDA likely inhibits SARS-CoV infection by targeting early stages of the replication cycle, namely, adsorption or penetration. In addition, we demonstrated that UDA neutralizes the virus infectivity, presumably by binding to the SARS-CoV spike (S) glycoprotein. Finally, the target molecule for the inhibition of virus

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

Science.gov (United States)

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

Science.gov (United States)

Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

2016-08-01

Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

Spike persistence and normalization in benign epilepsy with centrotemporal spikes - Implications for management.

Science.gov (United States)

Kim, Hunmin; Kim, Soo Yeon; Lim, Byung Chan; Hwang, Hee; Chae, Jong-Hee; Choi, Jieun; Kim, Ki Joong; Dlugos, Dennis J

2018-05-10

This study was performed 1) to determine the timing of spike normalization in patients with benign epilepsy with centrotemporal spikes (BECTS); 2) to identify relationships between age of seizure onset, age of spike normalization, years of spike persistence and treatment; and 3) to assess final outcomes between groups of patients with or without spikes at the time of medication tapering. Retrospective analysis of BECTS patients confirmed by clinical data, including age of onset, seizure semiology and serial electroencephalography (EEG) from diagnosis to remission. Age at spike normalization, years of spike persistence, and time of treatment onset to spike normalization were assessed. Final seizure and EEG outcome were compared between the groups with or without spikes at the time of AED tapering. One hundred and thirty-four patients were included. Mean age at seizure onset was 7.52 ± 2.11 years. Mean age at spike normalization was 11.89 ± 2.11 (range: 6.3-16.8) years. Mean time of treatment onset to spike normalization was 4.11 ± 2.13 (range: 0.24-10.08) years. Younger age of seizure onset was correlated with longer duration of spike persistence (r = -0.41, p < 0.001). In treated patients, spikes persisted for 4.1 ± 1.95 years, compared with 2.9 ± 1.97 years in untreated patients. No patients had recurrent seizures after AED was discontinued, regardless of the presence/absence of spikes at time of AED tapering. Years of spike persistence was longer in early onset BECTS patients. Treatment with AEDs did not shorten years of spike persistence. Persistence of spikes at time of treatment withdrawal was not associated with seizure recurrence. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

DEFF Research Database (Denmark)

Sandholt, Inge; Skriver, Henning

1999-01-01

The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

Expression, purification and crystallization of the SARS-CoV macro domain

International Nuclear Information System (INIS)

Malet, Hélène; Dalle, Karen; Brémond, Nicolas; Tocque, Fabienne; Blangy, Stéphanie; Campanacci, Valérie; Coutard, Bruno; Grisel, Sacha; Lichière, Julie; Lantez, Violaine; Cambillau, Christian; Canard, Bruno; Egloff, Marie-Pierre

2006-01-01

The SARS-CoV macro domain was expressed, purified and crystallized. Selenomethionine-labelled crystals diffracted to 1.8 Å resolution. Macro domains or X domains are found as modules of multidomain proteins, but can also constitute a protein on their own. Recently, biochemical and structural studies of cellular macro domains have been performed, showing that they are active as ADP-ribose-1′′-phosphatases. Macro domains are also present in a number of positive-stranded RNA viruses, but their precise function in viral replication is still unknown. The major human pathogen severe acute respiratory syndrome coronavirus (SARS-CoV) encodes 16 non-structural proteins (nsps), one of which (nsp3) encompasses a macro domain. The SARS-CoV nsp3 gene region corresponding to amino acids 182–355 has been cloned, expressed in Escherichia coli, purified and crystallized. The crystals belong to space group P2 1 , with unit-cell parameters a = 37.5, b = 55.6, c = 108.9 Å, β = 91.4°, and the asymmetric unit contains either two or three molecules. Both native and selenomethionine-labelled crystals diffract to 1.8 Å

Expression, purification and crystallization of the SARS-CoV macro domain

Energy Technology Data Exchange (ETDEWEB)

Malet, Hélène; Dalle, Karen; Brémond, Nicolas; Tocque, Fabienne; Blangy, Stéphanie; Campanacci, Valérie; Coutard, Bruno; Grisel, Sacha; Lichière, Julie; Lantez, Violaine; Cambillau, Christian; Canard, Bruno; Egloff, Marie-Pierre, E-mail: marie-pierre.egloff@afmb.univ-mrs.fr [Centre National de la Recherche Scientifique and Universités d’Aix-Marseille I et II, UMR 6098, Architecture et Fonction des Macromolécules Biologiques, UMR 6098-Case 932, 163 Avenue de Luminy, 13288 Marseille CEDEX 9 (France)

2006-04-01

The SARS-CoV macro domain was expressed, purified and crystallized. Selenomethionine-labelled crystals diffracted to 1.8 Å resolution. Macro domains or X domains are found as modules of multidomain proteins, but can also constitute a protein on their own. Recently, biochemical and structural studies of cellular macro domains have been performed, showing that they are active as ADP-ribose-1′′-phosphatases. Macro domains are also present in a number of positive-stranded RNA viruses, but their precise function in viral replication is still unknown. The major human pathogen severe acute respiratory syndrome coronavirus (SARS-CoV) encodes 16 non-structural proteins (nsps), one of which (nsp3) encompasses a macro domain. The SARS-CoV nsp3 gene region corresponding to amino acids 182–355 has been cloned, expressed in Escherichia coli, purified and crystallized. The crystals belong to space group P2{sub 1}, with unit-cell parameters a = 37.5, b = 55.6, c = 108.9 Å, β = 91.4°, and the asymmetric unit contains either two or three molecules. Both native and selenomethionine-labelled crystals diffract to 1.8 Å.

SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

Science.gov (United States)

Wassermann, Anne Mai; Haebel, Peter; Weskamp, Nils; Bajorath, Jürgen

2012-07-23

We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

Vented spikes improve delivery from intravenous bags with no air headspace.

Science.gov (United States)

Galush, William J; Horst, Travis A

2015-07-01

Flexible plastic bags are the container of choice for most intravenous (i.v.) infusions. Under certain circumstances, however, the air-liquid interface present in these i.v. bags can lead to physical instability of protein biopharmaceuticals, resulting in product aggregation. In principle, the air headspace present in the bags can be removed to increase drug stability, but experiments described here show that this can result in incomplete draining of solution from the bag using gravity delivery, or generation of negative pressure in the bag when an infusion pump is used. It is expected that these issues could lead to incomplete delivery of medication to patients or pump-related problems, respectively. However, here it is shown that contrary to the standard pharmacy practice of using nonvented spikes with i.v. bags, the use of vented spikes with i.v. bags that lack air headspace allows complete delivery of the dose solution without impacting the physical stability of a protein-based drug. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space

Directory of Open Access Journals (Sweden)

Kan Li

2018-04-01

Full Text Available This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM speech processing as well as neuromorphic implementations based on spiking neural network (SNN, yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR regime.

Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space.

Science.gov (United States)

Li, Kan; Príncipe, José C

2018-01-01

This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM) speech processing as well as neuromorphic implementations based on spiking neural network (SNN), yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR) or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC) front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR) regime.

The Performance Analysis Based on SAR Sample Covariance Matrix

Directory of Open Access Journals (Sweden)

Esra Erten

2012-03-01

Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.

Neural spike sorting using iterative ICA and a deflation-based approach.

Science.gov (United States)

Tiganj, Z; Mboup, M

2012-12-01

We propose a spike sorting method for multi-channel recordings. When applied in neural recordings, the performance of the independent component analysis (ICA) algorithm is known to be limited, since the number of recording sites is much lower than the number of neurons. The proposed method uses an iterative application of ICA and a deflation technique in two nested loops. In each iteration of the external loop, the spiking activity of one neuron is singled out and then deflated from the recordings. The internal loop implements a sequence of ICA and sorting for removing the noise and all the spikes that are not fired by the targeted neuron. Then a final step is appended to the two nested loops in order to separate simultaneously fired spikes. We solve this problem by taking all possible pairs of the sorted neurons and apply ICA only on the segments of the signal during which at least one of the neurons in a given pair was active. We validate the performance of the proposed method on simulated recordings, but also on a specific type of real recordings: simultaneous extracellular-intracellular. We quantify the sorting results on the extracellular recordings for the spikes that come from the neurons recorded intracellularly. The results suggest that the proposed solution significantly improves the performance of ICA in spike sorting.

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

Visible Earthquakes: a web-based tool for visualizing and modeling InSAR earthquake data

Science.gov (United States)

Funning, G. J.; Cockett, R.

2012-12-01

InSAR (Interferometric Synthetic Aperture Radar) is a technique for measuring the deformation of the ground using satellite radar data. One of the principal applications of this method is in the study of earthquakes; in the past 20 years over 70 earthquakes have been studied in this way, and forthcoming satellite missions promise to enable the routine and timely study of events in the future. Despite the utility of the technique and its widespread adoption by the research community, InSAR does not feature in the teaching curricula of most university geoscience departments. This is, we believe, due to a lack of accessibility to software and data. Existing tools for the visualization and modeling of interferograms are often research-oriented, command line-based and/or prohibitively expensive. Here we present a new web-based interactive tool for comparing real InSAR data with simple elastic models. The overall design of this tool was focused on ease of access and use. This tool should allow interested nonspecialists to gain a feel for the use of such data and greatly facilitate integration of InSAR into upper division geoscience courses, giving students practice in comparing actual data to modeled results. The tool, provisionally named 'Visible Earthquakes', uses web-based technologies to instantly render the displacement field that would be observable using InSAR for a given fault location, geometry, orientation, and slip. The user can adjust these 'source parameters' using a simple, clickable interface, and see how these affect the resulting model interferogram. By visually matching the model interferogram to a real earthquake interferogram (processed separately and included in the web tool) a user can produce their own estimates of the earthquake's source parameters. Once satisfied with the fit of their models, users can submit their results and see how they compare with the distribution of all other contributed earthquake models, as well as the mean and median

Solving constraint satisfaction problems with networks of spiking neurons

Directory of Open Access Journals (Sweden)

Zeno eJonke

2016-03-01

Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

Directory of Open Access Journals (Sweden)

Dongqing Peng

2016-11-01

Full Text Available Based on Time-Frequency (TF analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach.

Characterization of large instabilities displacements using Ground-Based InSAR

Science.gov (United States)

Rouyet, L.; Kristensen, L.; Derron, M.-H.; Michoud, C.; Blikra, L. H.; Jaboyedoff, M.

2012-04-01

A master thesis in progress at the Lausanne University (IGAR) in cooperation with the Åknes/Tafjord Early Warning Centre in Norway aims to characterize various instabilities displacements using Ground-Based Interferometric Synthetic Aperture Radar system (GB-InSAR). The main goal is to evaluate the potential of GB-InSAR to determine displacement velocities and mechanical behaviours of several large rock instabilities in Norway. GB-InSAR data are processed and interpreted for three case studies. The first test site is the unstable complex area of Mannen located in the Romsdalen valley (Møre og Romsdal county), threatening infrastructures and potentially able to cause a debacle event downstream. Its total volume is estimated to 15-25 mill m3. Mannen instability is monitored permanently with GB-InSAR since February 2010 and shows displacements towards the radar up to -8 mm per month during the most sensitive period. Børa area located on the southwest side of Mannen instability shows also some signs of activity. It monitored temporarily between August and October 2011 and could help to understand the behaviour of Mannen site. The second, Indre Nordnes rockslide in Lyngenfjord (Troms county), is directly located above an important fjord in North Norway causing a significant risk of tsunami. The volume is estimated to be around 10-15 mill m3. The site was monitored temporarily between June and August 2011. The data show displacements towards the radar up to -12 mm in 2 weeks. The third case concerns rock falls along the road between Oppdølsstranda and Sunndalsøra (Møre og Romsdal county). Even if the volume of rock is less important than the first two cases, rock falls are an important problem for the road 70 underneath. Several campaigns are done between beginning of 2010 and end of 2011. In June 2011 an important rock fall occurs in an area where significant movements were previously detected by GB-InSAR. In order to understand the behaviour of these

Introduction to spiking neural networks: Information processing, learning and applications.

Science.gov (United States)

Ponulak, Filip; Kasinski, Andrzej

2011-01-01

The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

Heterogeneity of Purkinje cell simple spike-complex spike interactions: zebrin- and non-zebrin-related variations.

Science.gov (United States)

Tang, Tianyu; Xiao, Jianqiang; Suh, Colleen Y; Burroughs, Amelia; Cerminara, Nadia L; Jia, Linjia; Marshall, Sarah P; Wise, Andrew K; Apps, Richard; Sugihara, Izumi; Lang, Eric J

2017-08-01

Cerebellar Purkinje cells (PCs) generate two types of action potentials, simple and complex spikes. Although they are generated by distinct mechanisms, interactions between the two spike types exist. Zebrin staining produces alternating positive and negative stripes of PCs across most of the cerebellar cortex. Thus, here we compared simple spike-complex spike interactions both within and across zebrin populations. Simple spike activity undergoes a complex modulation preceding and following a complex spike. The amplitudes of the pre- and post-complex spike modulation phases were correlated across PCs. On average, the modulation was larger for PCs in zebrin positive regions. Correlations between aspects of the complex spike waveform and simple spike activity were found, some of which varied between zebrin positive and negative PCs. The implications of the results are discussed with regard to hypotheses that complex spikes are triggered by rises in simple spike activity for either motor learning or homeostatic functions. Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the

A neural network detection model of spilled oil based on the texture analysis of SAR image

Science.gov (United States)

An, Jubai; Zhu, Lisong

2006-01-01

A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

Pressurized water reactor iodine spiking behavior under power transient conditions

International Nuclear Information System (INIS)

Ho, J.C.

1992-01-01

The most accepted theory explaining the cause of pressurized water reactor iodine spiking is steam formation and condensation in damaged fuel rods. The phase transformation of the primary coolant from water to steam and back again is believed to cause the iodine spiking phenomenon. But due to the complex nature of the phenomenon, a comprehensive model of the behavior has not yet been successfully developed. This paper presents a new model based on an empirical approach, which gives a first-order estimation of the peak iodine spiking magnitude. Based on the proposed iodine spiking model, it is apparent that it is feasible to derive a correlation using the plant operating data base to monitor and control the peak iodine spiking magnitude

Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India

OpenAIRE

Pazhanivelan, S.; Kannan, P.; Christy Nirmala Mary, P.; Subramanian, E.; Jeyaraman, S.; Nelson, A.; Setiyono, T.; Holecz, F.; Barbieri, M.; Yadav, M.

2015-01-01

Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used...

Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses

International Nuclear Information System (INIS)

Cofré, Rodrigo; Cessac, Bruno

2013-01-01

We investigate the effect of electric synapses (gap junctions) on collective neuronal dynamics and spike statistics in a conductance-based integrate-and-fire neural network, driven by Brownian noise, where conductances depend upon spike history. We compute explicitly the time evolution operator and show that, given the spike-history of the network and the membrane potentials at a given time, the further dynamical evolution can be written in a closed form. We show that spike train statistics is described by a Gibbs distribution whose potential can be approximated with an explicit formula, when the noise is weak. This potential form encompasses existing models for spike trains statistics analysis such as maximum entropy models or generalized linear models (GLM). We also discuss the different types of correlations: those induced by a shared stimulus and those induced by neurons interactions

Wavelet Filter Banks for Super-Resolution SAR Imaging

Science.gov (United States)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

Science.gov (United States)

Bardi, Federica; Frodella, William; Ciampalini, Andrea; Bianchini, Silvia; Del Ventisette, Chiara; Gigli, Giovanni; Fanti, Riccardo; Moretti, Sandro; Basile, Giuseppe; Casagli, Nicola

2014-10-01

The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty-clayey sedimentary cover. In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques. PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14 min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to

Spiking Neural P Systems with Communication on Request.

Science.gov (United States)

Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

2017-12-01

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

Fast Superpixel Segmentation Algorithm for PolSAR Images

Directory of Open Access Journals (Sweden)

Zhang Yue

2017-10-01

Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

SARS - Diagnosis

Indian Academy of Sciences (India)

SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

Guided SAR image despeckling with probabilistic non local weights

Science.gov (United States)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Urban Monitoring Based on SENTINEL-1 Data Using Permanent Scatterer Interferometry and SAR Tomography

Science.gov (United States)

Crosetto, M.; Budillon, A.; Johnsy, A.; Schirinzi, G.; Devanthéry, N.; Monserrat, O.; Cuevas-González, M.

2018-04-01

A lot of research and development has been devoted to the exploitation of satellite SAR images for deformation measurement and monitoring purposes since Differential Interferometric Synthetic Apertura Radar (InSAR) was first described in 1989. In this work, we consider two main classes of advanced DInSAR techniques: Persistent Scatterer Interferometry and Tomographic SAR. Both techniques make use of multiple SAR images acquired over the same site and advanced procedures to separate the deformation component from the other phase components, such as the residual topographic component, the atmospheric component, the thermal expansion component and the phase noise. TomoSAR offers the advantage of detecting either single scatterers presenting stable proprieties over time (Persistent Scatterers) and multiple scatterers interfering within the same range-azimuth resolution cell, a significant improvement for urban areas monitoring. This paper addresses a preliminary inter-comparison of the results of both techniques, for a test site located in the metropolitan area of Barcelona (Spain), where interferometric Sentinel-1 data were analysed.

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

Science.gov (United States)

Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling.

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

DEFF Research Database (Denmark)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.

2016-01-01

and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states......Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from...... visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary...

SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

Directory of Open Access Journals (Sweden)

Wu Yiquan

2017-08-01

Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

Bistatic sAR data processing algorithms

CERN Document Server

Qiu, Xiaolan; Hu, Donghui

2013-01-01

Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so sign

Flood extent and water level estimation from SAR using data-model integration

Science.gov (United States)

Ajadi, O. A.; Meyer, F. J.

2017-12-01

Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

Science.gov (United States)

Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

2016-06-01

Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

Directory of Open Access Journals (Sweden)

I. Schvartzman

2016-06-01

Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

Span: spike pattern association neuron for learning spatio-temporal spike patterns.

Science.gov (United States)

Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

2012-08-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

Spike sorting for polytrodes: a divide and conquer approach

Directory of Open Access Journals (Sweden)

Nicholas V. Swindale

2014-02-01

Full Text Available In order to determine patterns of neural activity, spike signals recorded by extracellular electrodes have to be clustered (sorted with the aim of ensuring that each cluster represents all the spikes generated by an individual neuron. Many methods for spike sorting have been proposed but few are easily applicable to recordings from polytrodes which may have 16 or more recording sites. As with tetrodes, these are spaced sufficiently closely that signals from single neurons will usually be recorded on several adjacent sites. Although this offers a better chance of distinguishing neurons with similarly shaped spikes, sorting is difficult in such cases because of the high dimensionality of the space in which the signals must be classified. This report details a method for spike sorting based on a divide and conquer approach. Clusters are initially formed by assigning each event to the channel on which it is largest. Each channel-based cluster is then sub-divided into as many distinct clusters as possible. These are then recombined on the basis of pairwise tests into a final set of clusters. Pairwise tests are also performed to establish how distinct each cluster is from the others. A modified gradient ascent clustering (GAC algorithm is used to do the clustering. The method can sort spikes with minimal user input in times comparable to real time for recordings lasting up to 45 minutes. Our results illustrate some of the difficulties inherent in spike sorting, including changes in spike shape over time. We show that some physiologically distinct units may have very similar spike shapes. We show that RMS measures of spike shape similarity are not sensitive enough to discriminate clusters that can otherwise be separated by principal components analysis. Hence spike sorting based on least-squares matching to templates may be unreliable. Our methods should be applicable to tetrodes and scaleable to larger multi-electrode arrays (MEAs.

Characterization of novel monoclonal antibodies against the MERS-coronavirus spike protein and their application in species-independent antibody detection by competitive ELISA.

Science.gov (United States)

Fukushi, Shuetsu; Fukuma, Aiko; Kurosu, Takeshi; Watanabe, Shumpei; Shimojima, Masayuki; Shirato, Kazuya; Iwata-Yoshikawa, Naoko; Nagata, Noriyo; Ohnishi, Kazuo; Ato, Manabu; Melaku, Simenew Keskes; Sentsui, Hiroshi; Saijo, Masayuki

2018-01-01

Since discovering the Middle East respiratory syndrome coronavirus (MERS-CoV) as a causative agent of severe respiratory illness in the Middle East in 2012, serological testing has been conducted to assess antibody responses in patients and to investigate the zoonotic reservoir of the virus. Although the virus neutralization test is the gold standard assay for MERS diagnosis and for investigating the zoonotic reservoir, it uses live virus and so must be performed in high containment laboratories. Competitive ELISA (cELISA), in which a labeled monoclonal antibody (MAb) competes with test serum antibodies for target epitopes, may be a suitable alternative because it detects antibodies in a species-independent manner. In this study, novel MAbs against the spike protein of MERS-CoV were produced and characterized. One of these MAbs was used to develop a cELISA. The cELISA detected MERS-CoV-specific antibodies in sera from MERS-CoV-infected rats and rabbits immunized with the spike protein of MERS-CoV. The MAb-based cELISA was validated using sera from Ethiopian dromedary camels. Relative to the neutralization test, the cELISA detected MERS-CoV-specific antibodies in 66 Ethiopian dromedary camels with a sensitivity and specificity of 98% and 100%, respectively. The cELISA and neutralization test results correlated well (Pearson's correlation coefficients=0.71-0.76, depending on the cELISA serum dilution). This cELISA may be useful for MERS epidemiological investigations on MERS-CoV infection. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Spiking Networks

NARCIS (Netherlands)

O'Connor, P.; Welling, M.

2016-01-01

We introduce an algorithm to do backpropagation on a spiking network. Our network is "spiking" in the sense that our neurons accumulate their activation into a potential over time, and only send out a signal (a "spike") when this potential crosses a threshold and the neuron is reset. Neurons only

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

Science.gov (United States)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a

Sketches of a hammer-impact, spiked-base, shear-wave source

Science.gov (United States)

Hasbrouck, W.P.

1983-01-01

Generation of shear waves in shallow seismic investigations (those to depths usually less than 100 m) can be accomplished by horizontally striking with a hammer either the end of a wood plank or metal structure embedded at the ground surface. The dimensioned sketches of this report are of a steel, hammer-impact, spiked-base, shear-wave source. It has been used on outcrops and in a desert environment and for conducting experiments on the effect of rotating source direction.

Combining pharmacophore fingerprints and PLS-discriminant analysis for virtual screening and SAR elucidation

DEFF Research Database (Denmark)

Askjær, Sune; Langgård, Morten

2008-01-01

The criterion of success for the initial stages of a ligand-based drug-discovery project is dual. First, a set of suitable lead compounds has to be identified. Second, a level of a preliminary structure-activity relationship (SAR) of the identified ligands has to be established in order to guide ...... by the protein-binding site known from X-ray complexes. The result of this analysis assists in explaining the efficiency of 2D pharmacophore fingerprints as descriptors in virtual screening....... the lead optimization toward a final drug candidate. This paper presents a combined approach to solving these two problems of ligand-based virtual screening and elucidation of SAR based on interplay between pharmacophore fingerprints and interpretation of PLS-discriminant analysis (PLS-DA) models....... The virtual screening capability of the PLS-DA method is compared to group fusion maximum similarity searching in a test using four graph-based pharmacophore fingerprints over a range of 10 diverse targets. The PLS-DA method was generally found to do better than the Smax method. The GpiDAPH3 and PCH...

Population-based Post-crisis Psychological Distress: An Example From the SARS Outbreak in Taiwan

Science.gov (United States)

Peng, Eugene Yu-Chang; Lee, Ming-Been; Tsai, Shang-Ta; Yang, Chih-Chien; Morisky, Donald Edward; Tsai, Liang-Ting; Weng, Ya-Ling; Lyu, Shu-Yu

2011-01-01

Background/Purpose As a result of the severe acute respiratory syndrome (SARS) pandemic, the World Health Organization placed Taiwan on the travel alert list from May 21 to July 5, 2003. The aim of this study was to explore the post-crisis psychological distress among residents in Taiwan after the SARS epidemic. Methods The target population consisted of a nationwide representative sample of residents aged ≥ 18 years. Data were collected using computer assisted telephone interview systems by stratified random sampling according to geographic area. The survey (n = 1278) was conducted in November 2003, about 4 months after resolution of the SARS crisis in Taiwan. The maximum deviation of sampling error at the 95% confidence level was ± 2.74%. Psychological distress was measured by a question related to subject’s changes in perception of life, plus the five-item Brief Symptom Rating Scale. Multivariate logistic regression was used to examine the correlation of psychological distress. Results About 9.2% of the participants reported that their perceptions of life became more pessimistic following the SARS crisis. The prevalence of psychiatric morbidity was 11.7%. Major predictors of higher levels of pessimism after the SARS epidemic included demographic factors, perception of SARS and pre-paredness, knowing people or having personal experiences of SARS-related discrimination, and individual worries and psychiatric morbidity. The correlates of symptomatic cases, as indicated by the five-item Brief Symptom Rating Scale, included age ≥ 50 years, senior high school graduate, and worries about recurrence of SARS. Conclusion Psychological distress was significantly correlated with demographic factors and perception regarding the SARS epidemic. It is suggested that marketing of mental health education should be segmented according to age and education level, which should enhance crisis communication for newly emerging infectious diseases among community populations

Using Common Spatial Distributions of Atoms to Relate Functionally Divergent Influenza Virus N10 and N11 Protein Structures to Functionally Characterized Neuraminidase Structures, Toxin Cell Entry Domains, and Non-Influenza Virus Cell Entry Domains

Science.gov (United States)

Weininger, Arthur; Weininger, Susan

2015-01-01

The ability to identify the functional correlates of structural and sequence variation in proteins is a critical capability. We related structures of influenza A N10 and N11 proteins that have no established function to structures of proteins with known function by identifying spatially conserved atoms. We identified atoms with common distributed spatial occupancy in PDB structures of N10 protein, N11 protein, an influenza A neuraminidase, an influenza B neuraminidase, and a bacterial neuraminidase. By superposing these spatially conserved atoms, we aligned the structures and associated molecules. We report spatially and sequence invariant residues in the aligned structures. Spatially invariant residues in the N6 and influenza B neuraminidase active sites were found in previously unidentified spatially equivalent sites in the N10 and N11 proteins. We found the corresponding secondary and tertiary structures of the aligned proteins to be largely identical despite significant sequence divergence. We found structural precedent in known non-neuraminidase structures for residues exhibiting structural and sequence divergence in the aligned structures. In N10 protein, we identified staphylococcal enterotoxin I-like domains. In N11 protein, we identified hepatitis E E2S-like domains, SARS spike protein-like domains, and toxin components shared by alpha-bungarotoxin, staphylococcal enterotoxin I, anthrax lethal factor, clostridium botulinum neurotoxin, and clostridium tetanus toxin. The presence of active site components common to the N6, influenza B, and S. pneumoniae neuraminidases in the N10 and N11 proteins, combined with the absence of apparent neuraminidase function, suggests that the role of neuraminidases in H17N10 and H18N11 emerging influenza A viruses may have changed. The presentation of E2S-like, SARS spike protein-like, or toxin-like domains by the N10 and N11 proteins in these emerging viruses may indicate that H17N10 and H18N11 sialidase-facilitated cell

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

Directory of Open Access Journals (Sweden)

Pietro Quaglio

2017-05-01

Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

Spike-based decision learning of Nash equilibria in two-player games.

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Johannes Friedrich

Full Text Available Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic and mixed (stochastic Nash equilibrium, respectively. In contrast, temporal-difference(TD-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

Decoding spikes in a spiking neuronal network

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)

2004-06-04

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.

Decoding spikes in a spiking neuronal network

International Nuclear Information System (INIS)

Feng Jianfeng; Ding, Mingzhou

2004-01-01

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs

Inherently stochastic spiking neurons for probabilistic neural computation

KAUST Repository

Al-Shedivat, Maruan

2015-04-01

Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

Importance of Neutralizing Monoclonal Antibodies Targeting Multiple Antigenic Sites on the Middle East Respiratory Syndrome Coronavirus Spike Glycoprotein To Avoid Neutralization Escape

Energy Technology Data Exchange (ETDEWEB)

Wang, Lingshu; Shi, Wei; Chappell, James D.; Joyce, M. Gordon; Zhang, Yi; Kanekiyo, Masaru; Becker, Michelle M.; van Doremalen, Neeltje; Fischer, Robert; Wang, Nianshuang; Corbett, Kizzmekia S.; Choe, Misook; Mason, Rosemarie D.; Van Galen, Joseph G.; Zhou, Tongqing; Saunders, Kevin O.; Tatti, Kathleen M.; Haynes, Lia M.; Kwong, Peter D.; Modjarrad, Kayvon; Kong, Wing-Pui; McLellan, Jason S.; Denison, Mark R.; Munster, Vincent J.; Mascola, John R.; Graham, Barney S.; Gallagher, Tom

2018-03-07

structurally defined probes for the MERS-CoV spike glycoprotein (S), the target for neutralizing antibodies, single B cells were sorted from a convalescent human and immunized nonhuman primates (NHPs). MAbs produced from paired immunoglobulin gene sequences were mapped to multiple epitopes within and outside the receptor-binding domain (RBD) and protected against lethal MERS infection in a murine model following passive immunization. Importantly, combining MAbs targeting distinct epitopes prevented viral neutralization escape from RBD-directed MAbs. These data suggest that antibody responses to multiple domains on CoV spike protein may improve immunity and will guide future vaccine and therapeutic development efforts.

Binding of the GTPase Sar1 to a Lipid Membrane Monolayer: Insertion and Orientation Studied by Infrared Reflection–Absorption Spectroscopy

Directory of Open Access Journals (Sweden)

Christian Schwieger

2017-11-01

Full Text Available Membrane-interacting proteins are polyphilic polymers that engage in dynamic protein–protein and protein–lipid interactions while undergoing changes in conformation, orientation and binding interfaces. Predicting the sites of interactions between such polypeptides and phospholipid membranes is still a challenge. One example is the small eukaryotic GTPase Sar1, which functions in phospholipid bilayer remodeling and vesicle formation as part of the multimeric coat protein complex (COPII. The membrane interaction of Sar1 is strongly dependent on its N-terminal 23 amino acids. By monolayer adsorption experiments and infrared reflection-absorption spectroscopy (IRRAS, we elucidate the role of lipids in inducing the amphipathicity of this N-terminal stretch, which inserts into the monolayer as an amphipathic helix (AH. The AH inserting angle is determined and is consistent with the philicities and spatial distribution of the amino acid monomers. Using an advanced method of IRRAS data evaluation, the orientation of Sar1 with respect to the lipid layer prior to the recruitment of further COPII proteins is determined. The result indicates that only a slight reorientation of the membrane-bound Sar1 is needed to allow coat assembly. The time-course of the IRRAS analysis corroborates a role of slow GTP hydrolysis in Sar1 desorption from the membrane.

Comparison of Classifier Architectures for Online Neural Spike Sorting.

Science.gov (United States)

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

A new supervised learning algorithm for spiking neurons.

Science.gov (United States)

Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

2013-06-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

Training Deep Spiking Neural Networks Using Backpropagation.

Science.gov (United States)

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains

Directory of Open Access Journals (Sweden)

Enrico Stein

2013-10-01

Full Text Available A two-component fully automated flood monitoring system is described and evaluated. This is a result of combining two individual flood services that are currently under development at DLR’s (German Aerospace Center Center for Satellite based Crisis Information (ZKI to rapidly support disaster management activities. A first-phase monitoring component of the system systematically detects potential flood events on a continental scale using daily-acquired medium spatial resolution optical data from the Moderate Resolution Imaging Spectroradiometer (MODIS. A threshold set controls the activation of the second-phase crisis component of the system, which derives flood information at higher spatial detail using a Synthetic Aperture Radar (SAR based satellite mission (TerraSAR-X. The proposed activation procedure finds use in the identification of flood situations in different spatial resolutions and in the time-critical and on demand programming of SAR satellite acquisitions at an early stage of an evolving flood situation. The automated processing chains of the MODIS (MFS and the TerraSAR-X Flood Service (TFS include data pre-processing, the computation and adaptation of global auxiliary data, thematic classification, and the subsequent dissemination of flood maps using an interactive web-client. The system is operationally demonstrated and evaluated via the monitoring two recent flood events in Russia 2013 and Albania/Montenegro 2013.

Keynote presentation : SAR systems

NARCIS (Netherlands)

Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

2011-01-01

Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.

Science.gov (United States)

Burroughs, Amelia; Wise, Andrew K; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y; Lang, Eric J; Apps, Richard; Cerminara, Nadia L

2017-01-01

Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes. Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets. The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear. We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number. This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition

Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

Directory of Open Access Journals (Sweden)

Michele Crosetto

2011-02-01

Full Text Available This paper is focused on spaceborne Differential Interferometric SAR (DInSAR for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors.

Information theoretic bounds for compressed sensing in SAR imaging

International Nuclear Information System (INIS)

Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

2014-01-01

Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

Science.gov (United States)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.; Roland, Per E.

2016-01-01

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. PMID:27582693

Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

Science.gov (United States)

Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

2016-01-01

Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

Amino acid changes in the spike protein of feline coronavirus correlate with systemic spread of virus from the intestine and not with feline infectious peritonitis.

Science.gov (United States)

Porter, Emily; Tasker, Séverine; Day, Michael J; Harley, Ross; Kipar, Anja; Siddell, Stuart G; Helps, Christopher R

2014-04-25

Recent evidence suggests that a mutation in the spike protein gene of feline coronavirus (FCoV), which results in an amino acid change from methionine to leucine at position 1058, may be associated with feline infectious peritonitis (FIP). Tissue and faecal samples collected post mortem from cats diagnosed with or without FIP were subjected to RNA extraction and quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) to detect FCoV RNA. In cats with FIP, 95% of tissue, and 81% of faecal samples were PCR-positive, as opposed to 22% of tissue, and 60% of faecal samples in cats without FIP. Relative FCoV copy numbers were significantly higher in the cats with FIP, both in tissues (P < 0.001) and faeces (P = 0.02). PCR-positive samples underwent pyrosequencing encompassing position 1058 of the FCoV spike protein. This identified a methionine codon at position 1058, consistent with the shedding of an enteric form of FCoV, in 77% of the faecal samples from cats with FIP, and in 100% of the samples from cats without FIP. In contrast, 91% of the tissue samples from cats with FIP and 89% from cats without FIP had a leucine codon at position 1058, consistent with a systemic form of FCoV. These results suggest that the methionine to leucine substitution at position 1058 in the FCoV spike protein is indicative of systemic spread of FCoV from the intestine, rather than a virus with the potential to cause FIP.

A 33fJ/Step SAR Capacitance-to-Digital Converter Using a Chain of Inverter-Based Amplifiers

KAUST Repository

Omran, Hesham

2016-11-16

A 12 - bit energy-efficient capacitive sensor interface circuit that fully relies on capacitance-domain successive approximation (SAR) technique is presented. Analysis shows that for SAR capacitance-to-digital converter (CDC) comparator offset voltage will result in parasitic-dependent conversion errors, which necessitates using an offset cancellation technique. Based on the presented analysis, a SAR CDC that uses a chain of cascode inverter-based amplifiers with near-threshold biasing is proposed to provide robust, energy-efficient, and fast operation. A hybrid coarse-fine capacitive digital-to-analog converter (CapDAC) achieves 11.7 - bit effective resolution, and provides 83% area saving compared to a conventional binary weighted implementation. The prototype fabricated in a 0.18μm CMOS technology is experimentally verified using MEMS capacitive pressure sensor. Experimental results show an energy efficiency figure-of-merit (FoM) of 33 f J/Step which outperforms the state-of-the-art. The CDC output is insensitive to analog references; thus, a very low temperature sensitivity of 2.3 ppm/°C is achieved without the need for calibration.

A 33fJ/Step SAR Capacitance-to-Digital Converter Using a Chain of Inverter-Based Amplifiers

KAUST Repository

Omran, Hesham; Alhoshany, Abdulaziz; Alahmadi, Hamzah; Salama, Khaled N.

2016-01-01

A 12 - bit energy-efficient capacitive sensor interface circuit that fully relies on capacitance-domain successive approximation (SAR) technique is presented. Analysis shows that for SAR capacitance-to-digital converter (CDC) comparator offset voltage will result in parasitic-dependent conversion errors, which necessitates using an offset cancellation technique. Based on the presented analysis, a SAR CDC that uses a chain of cascode inverter-based amplifiers with near-threshold biasing is proposed to provide robust, energy-efficient, and fast operation. A hybrid coarse-fine capacitive digital-to-analog converter (CapDAC) achieves 11.7 - bit effective resolution, and provides 83% area saving compared to a conventional binary weighted implementation. The prototype fabricated in a 0.18μm CMOS technology is experimentally verified using MEMS capacitive pressure sensor. Experimental results show an energy efficiency figure-of-merit (FoM) of 33 f J/Step which outperforms the state-of-the-art. The CDC output is insensitive to analog references; thus, a very low temperature sensitivity of 2.3 ppm/°C is achieved without the need for calibration.

LTE modem power consumption, SAR and RF signal strength emulation

DEFF Research Database (Denmark)

Musiige, Deogratius; Vincent, Laulagnet; Anton, François

2012-01-01

This paper presents a new methodology for emulating the LTE modem power consumption, emitted SAR and RF signal strength when transmitting an LTE signal. The inputs of the methodology are: modem logical/protocol commands, time advance, near-field specifier, and antenna characteristics. The power...... emulation model(s) are computed by a two layer 451 neural network based on physical power measurements. SAR is emulated by polynomial interpolation models based on FDTD simulations. The accuracies of the mathematical function approximations for the emulation models of power and SAR are 5.19% and 3...

Modulation of the spike activity of neocortex neurons during a conditioned reflex.

Science.gov (United States)

Storozhuk, V M; Sanzharovskii, A V; Sachenko, V V; Busel, B I

2000-01-01

Experiments were conducted on cats to study the effects of iontophoretic application of glutamate and a number of modulators on the spike activity of neurons in the sensorimotor cortex during a conditioned reflex. These studies showed that glutamate, as well as exerting a direct influence on neuron spike activity, also had a delayed facilitatory action lasting 10-20 min after iontophoresis was finished. Adrenomimetics were found to have a double modulatory effect on intracortical glutamate connections: inhibitory and facilitatory effects were mediated by beta1 and beta2 adrenoceptors respectively. Although dopamine, like glutamate, facilitated neuron spike activity during the period of application, the simultaneous facilitatory actions of glutamate and L-DOPA were accompanied by occlusion of spike activity, and simultaneous application of glutamate and haloperidol suppressed spike activity associated with the conditioned reflex response. Facilitation thus appears to show a significant level of dependence on metabotropic glutamate receptors which, like dopamine receptors, are linked to the intracellular medium via Gi proteins.

An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

Directory of Open Access Journals (Sweden)

Anup Vanarse

2017-11-01

Full Text Available The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses.

Global Rapid Flood Mapping System with Spaceborne SAR Data

Science.gov (United States)

Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

2017-12-01

As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

The Seamless SAR Archive (SSARA) Project and Other SAR Activities at UNAVCO

Science.gov (United States)

Baker, S.; Crosby, C. J.; Meertens, C. M.; Fielding, E. J.; Bryson, G.; Buechler, B.; Nicoll, J.; Baru, C.

2014-12-01

The seamless synthetic aperture radar archive (SSARA) implements a seamless distributed access system for SAR data and derived data products (i.e. interferograms). SSARA provides a unified application programming interface (API) for SAR data search and results at the Alaska Satellite Facility and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives. Interest from the international community has prompted an effort to incorporate ESA's Virtual Archive 4 Geohazard Supersites and Natural Laboratories (GSNL) collections and other archives into the federated query service. SSARA also provides Digital Elevation Model access for topographic correction via a simple web service through OpenTopography and tropospheric correction products through JPL's OSCAR service. Additionally, UNAVCO provides data storage capabilities for WInSAR PIs with approved TerraSAR-X and ALOS-2 proposals which allows easier distribution to US collaborators on associated proposals and facilitates data access through the SSARA web services. Further work is underway to incorporate federated data discovery for GSNL across SAR, GPS, and seismic datasets provided by web services from SSARA, GSAC, and COOPEUS.

Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

Directory of Open Access Journals (Sweden)

Xiaoli Ding

2009-02-01

Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

Fitting neuron models to spike trains

Directory of Open Access Journals (Sweden)

Cyrille eRossant

2011-02-01

Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

From genome to antivirals: SARS as a test tube.

Science.gov (United States)

Kliger, Yossef; Levanon, Erez Y; Gerber, Doron

2005-03-01

The severe acute respiratory syndrome (SARS) epidemic brought into the spotlight the need for rapid development of effective anti-viral drugs against newly emerging viruses. Researchers have leveraged the 20-year battle against AIDS into a variety of possible treatments for SARS. Most prominently, based solely on viral genome information, silencers of viral genes, viral-enzyme blockers and viral-entry inhibitors were suggested as potential therapeutic agents for SARS. In particular, inhibitors of viral entry, comprising therapeutic peptides, were based on the recently launched anti-HIV drug enfuvirtide. This could represent one of the most direct routes from genome sequencing to the discovery of antiviral drugs.

Multi-look polarimetric SAR image filtering using simulated annealing

DEFF Research Database (Denmark)

Schou, Jesper

2000-01-01

Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

Automatic EEG spike detection.

Science.gov (United States)

Harner, Richard

2009-10-01

Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

Directory of Open Access Journals (Sweden)

Tingting Jin

2017-04-01

Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

Directory of Open Access Journals (Sweden)

W. Lu

2017-09-01

Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

SarA is a negative regulator of Staphylococcus epidermidis biofilm formation

DEFF Research Database (Denmark)

Martin, Christer; Heinze, C.; Busch, M.

2012-01-01

Biofilm formation is essential for Staphylococcus epidermidis pathogenicity in implant-associated infections. Nonetheless, large proportions of invasive S. epidermidis isolates fail to show accumulative biofilm growth in vitro. We here tested the hypothesis that this apparent paradox is related...... virulence. Genetic analysis revealed that inactivation of sarA induced biofilm formation via over-expression of the giant 1 MDa extracellular matrix binding protein (Embp), serving as an intercellular adhesin. In addition to Embp, increased extracellular DNA (eDNA) release significantly contributed...... to biofilm formation in mutant 1585ΔsarA. Increased eDNA amounts indirectly resulted from up-regulation of metalloprotease SepA, leading to boosted processing of major autolysin AtlE, in turn inducing augmented autolysis and release of chromosomal DNA. Hence, this study identifies sarA as a negative...

SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

Directory of Open Access Journals (Sweden)

A. Rezaeian

2015-12-01

Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

Science.gov (United States)

Rezaeian, A.; Homayouni, S.; Safari, A.

2015-12-01

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Severe acute respiratory syndrome (SARS)

Science.gov (United States)

SARS; Respiratory failure - SARS ... Complications may include: Respiratory failure Liver failure Heart failure ... 366. McIntosh K, Perlman S. Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). ...

Comparison of electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially polluted soil

DEFF Research Database (Denmark)

Ottosen, Lisbeth M.; Lepkova, Katarina; Kubal, Martin

2006-01-01

Electrokinetic remediation methods for removal of heavy metals from polluted soils have been subjected for quite intense research during the past years since these methods are well suitable for fine-grained soils where other remediation methods fail. Electrodialytic remediation is an electrokinetic...... remediation method which is based on applying an electric DC field and the use of ion exchange membranes that ensures the main transport of heavy metals to be out of the pollutes soil. An experimental investigation was made with electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially...... polluted soil under the same operational conditions (constant current density 0.2 mA/cm2 and duration 28 days). The results of the present paper show that caution must be taken when generalising results obtained in spiked kaolinite to remediation of industrially polluted soils, as it was shown...

Long-term persistence of robust antibody and cytotoxic T cell responses in recovered patients infected with SARS coronavirus.

Directory of Open Access Journals (Sweden)

Taisheng Li

2006-12-01

Full Text Available Most of the individuals infected with SARS coronavirus (SARS-CoV spontaneously recovered without clinical intervention. However, the immunological correlates associated with patients' recovery are currently unknown. In this report, we have sequentially monitored 30 recovered patients over a two-year period to characterize temporal changes in SARS-CoV-specific antibody responses as well as cytotoxic T cell (CTL responses. We have found persistence of robust antibody and CTL responses in all of the study subjects throughout the study period, with a moderate decline one year after the onset of symptoms. We have also identified two potential major CTL epitopes in N proteins based on ELISPOT analysis of pooled peptides. However, despite the potent immune responses and clinical recovery, peripheral lymphocyte counts in the recovered patients have not yet been restored to normal levels. In summary, our study has, for the first time, characterized the temporal and dynamic changes of humoral and CTL responses in the natural history of SARS-recovered individuals, and strongly supports the notion that high and sustainable levels of immune responses correlate strongly with the disease outcome. Our findings have direct implications for future design and development of effective therapeutic agents and vaccines against SARS-CoV infection.

Ka-band InSAR Imaging and Analysis Based on IMU Data

Directory of Open Access Journals (Sweden)

Shi Jun

2014-02-01

Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

What is missing? An operational inundation mapping framework by SAR data

Science.gov (United States)

Shen, X.; Anagnostou, E. N.; Zeng, Z.; Kettner, A.; Hong, Y.

2017-12-01

Compared to optical sensors, synthetic aperture radar (SAR) works all-day all-weather. In addition, its spatial resolution does not decrease with the height of the platform and is thus applicable to a range of important studies. However, existing studies did not address the operational demands of real-time inundation mapping. The direct proof is that no water body product exists for any SAR-based satellites. Then what is missing between science and products? Automation and quality. What makes it so difficult to develop an operational inundation mapping technique based on SAR data? Spectrum-wise, unlike optical water indices such as MNDWI, AWEI etc., where a relative constant threshold may apply across acquisition of images, regions and sensors, the threshold to separate water from non-water pixels in each SAR images has to be individually chosen. The optimization of the threshold is the first obstacle to the automation of the SAR data algorithm. Morphologically, the quality and reliability of the results have been compromised by over-detection caused by smooth surface and shadowing area, the noise-like speckle and under-detection caused by strong-scatter disturbance. In this study, we propose a three-step framework that addresses all aforementioned issues of operational inundation mapping by SAR data. The framework consists of 1) optimization of Wishart distribution parameters of single/dual/fully-polarized SAR data, 2) morphological removal of over-detection, and 3) machine-learning based removal of under-detection. The framework utilizes not only the SAR data, but also the synergy of digital elevation model (DEM), and optical sensor-based products of fine resolution, including the water probability map, land cover classification map (optional), and river width. The framework has been validated throughout multiple areas in different parts of the world using different satellite SAR data and globally available ancillary data products. Therefore, it has the potential

Mapping mountain meadow with high resolution and polarimetric SAR data

International Nuclear Information System (INIS)

Tian, Bangsen; Li, Zhen; Xu, Juan; Fu, Sitao; Liu, Jiuli

2014-01-01

This paper presents a method to map the large grassland in the eastern margin of the Tibetan Plateau with the high resolution polarimetric SAR (PolSAR) imagery. When PolSAR imagery is used for land cover classification, the brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. The objective of this paper is twofold: (1) we first extend the theory of SAR terrain correction to the polarimetric case, to utilize the entire available polarimetric signature, where correction is performed explicitly based on a matrix format like covariance matrix. (2) Next, the orthoectified PolSAR is applied to classify mountain meadow and investigate the potential of PolSAR in mapping grassland. In this paper, the gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product. Secondly, the impact of radiometric correction upon classification accuracy is investigated. A supervised classification is performed on the orthorectified Radarsat-2 PolSAR to map the spatial distribution of meadow and evaluate monitoring capabilities of mountain meadow

Discovery of a novel bottlenose dolphin coronavirus reveals a distinct species of marine mammal coronavirus in Gammacoronavirus.

Science.gov (United States)

Woo, Patrick C Y; Lau, Susanna K P; Lam, Carol S F; Tsang, Alan K L; Hui, Suk-Wai; Fan, Rachel Y Y; Martelli, Paolo; Yuen, Kwok-Yung

2014-01-01

While gammacoronaviruses mainly comprise infectious bronchitis virus (IBV) and its closely related bird coronaviruses (CoVs), the only mammalian gammacoronavirus was discovered from a white beluga whale (beluga whale CoV [BWCoV] SW1) in 2008. In this study, we discovered a novel gammacoronavirus from fecal samples from three Indo-Pacific bottlenose dolphins (Tursiops aduncus), which we named bottlenose dolphin CoV (BdCoV) HKU22. All the three BdCoV HKU22-positive samples were collected on the same date, suggesting a cluster of infection, with viral loads of 1 × 10(3) to 1 × 10(5) copies per ml. Clearance of virus was associated with a specific antibody response against the nucleocapsid of BdCoV HKU22. Complete genome sequencing and comparative genome analysis showed that BdCoV HKU22 and BWCoV SW1 have similar genome characteristics and structures. Their genome size is about 32,000 nucleotides, the largest among all CoVs, as a result of multiple unique open reading frames (NS5a, NS5b, NS5c, NS6, NS7, NS8, NS9, and NS10) between their membrane (M) and nucleocapsid (N) protein genes. Although comparative genome analysis showed that BdCoV HKU22 and BWCoV SW1 should belong to the same species, a major difference was observed in the proteins encoded by their spike (S) genes, which showed only 74.3 to 74.7% amino acid identities. The high ratios of the number of synonymous substitutions per synonymous site (Ks) to the number of nonsynonymous substitutions per nonsynonymous site (Ka) in multiple regions of the genome, especially the S gene (Ka/Ks ratio, 2.5), indicated that BdCoV HKU22 may be evolving rapidly, supporting a recent transmission event to the bottlenose dolphins. We propose a distinct species, Cetacean coronavirus, in Gammacoronavirus, to include BdCoV HKU22 and BWCoV SW1, whereas IBV and its closely related bird CoVs represent another species, Avian coronavirus, in Gammacoronavirus.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

SARS CTL vaccine candidates; HLA supertype-, genome-wide scanning and biochemical validation

DEFF Research Database (Denmark)

Sylvester-Hvid, C; Nielsen, M; Lamberth, K

2004-01-01

. Exact knowledge of how the immune system handles protein antigens would allow for the identification of such linear sequences directly from genomic/proteomic sequence information (Lauemoller et al., Rev Immunogenet 2001: 2: 477-91). The latter was recently established when a causative coronavirus (SARS...... of the HLA supertypes and identified almost 100 potential vaccine candidates. These should be further validated in SARS survivors and used for vaccine formulation. We suggest that immunobioinformatics may become a fast and valuable tool in rational vaccine design....

SARS CTL vaccine candidates; HLA supertype-, genome-wide scanning and biochemical validation

DEFF Research Database (Denmark)

Sylvester-Hvid, C.; Nielsen, Morten; Lamberth, K.

2004-01-01

. Exact knowledge of how the immune system handles protein antigens would allow for the identification of such linear sequences directly, from genomic/proteomic sequence information (Lauemoller et al., Rev Immunogenet 2001: 2: 477-91). The latter was recently established when a causative coronavirus (SARS...... of the HLA supertypes and identified almost 100 potential vaccine candidates. These should be further validated in SARS survivors and used for vaccine formulation. We suggest that immunobioinformatics may become a fast and valuable tool in rational vaccine design....

Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map

Directory of Open Access Journals (Sweden)

CHEN Min

2016-03-01

Full Text Available A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.

Assessment of Polarimetric SAR Interferometry for Improving Ship Classification based on Simulated Data

Directory of Open Access Journals (Sweden)

Jordi J. Mallorqui

2008-12-01

Full Text Available This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive scattering studies. The results have revealed, first, vessels’ geometries can be described by specific combinations of Permanent Polarimetric Scatterers (PePS and, second, each type of vessel could be characterized by a particular spatial and polarimetric distribution of PePS. Such properties have been recently exploited to propose a new Vessel Classification Algorithm (VCA working with POLInSAR data, which, according to several simulation tests, may provide promising performance in real scenarios. Along the paper, explanation of the main steps summarizing the whole research activity carried out with ships and GRECOSAR are provided as well as examples of the main results and VCA validation tests. Special attention will be devoted to the new improvements achieved, which are related to simulations processing a new and highly realistic sea surface model. The paper will show that, for POLInSAR data with fine resolution, VCA can help to classify ships with notable robustness under diverse and adverse observation conditions.

Multineuron spike train analysis with R-convolution linear combination kernel.

Science.gov (United States)

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

Directory of Open Access Journals (Sweden)

J. Q. Zhao

2016-06-01

Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

SAR compliance assessment of PMR 446 and FRS walkie-talkies.

Science.gov (United States)

Vermeeren, Günter; Joseph, Wout; Martens, Luc

2015-10-01

The vast amount of studies on radiofrequency dosimetry deal with exposure due to mobile devices and base station antennas for cellular communication systems. This study investigates compliance of walkie-talkies to exposure guidelines established by the International Commission on Non-Ionizing Radiation Protection and the Federal Communications Committee. The generic walkie-talkie consisted of a helical antenna and a ground plane and was derived by reverse engineering of a commercial walkie-talkie. Measured and simulated values of antenna characteristics and electromagnetic near fields of the generic walkie-talkie were within 2% and 8%, respectively. We also validated normalized electromagnetic near fields of the generic walkie-talkie against a commercial device and observed a very good agreement (deviation based on magnetic near field. Finally, we found that SAR of commercial devices is within current SAR limits for general public exposure for a worst-case duty cycle of 100%, that is, about 3 times and 6 times lower than the limit on the 1 g SAR (1.6 W/kg) and 10 g SAR (2 W/kg), respectively. But, an effective radiated power as specified by the Private Mobile Radio at 446 MHz (PMR 446) radio standard can cause localized SAR exceeding SAR limits for 1 g of tissue. © 2015 Wiley Periodicals, Inc.

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

Science.gov (United States)

Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Decoding spatiotemporal spike sequences via the finite state automata dynamics of spiking neural networks

International Nuclear Information System (INIS)

Jin, Dezhe Z

2008-01-01

Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences

Calibration of SAR probes in waveguide at 900 MHz

International Nuclear Information System (INIS)

Jokela, K.; Puranen, L.; Hyysalo, P.

1998-01-01

The radiation safety tests for hand-held mobile phones require precise calibration of the small electric field probes used for the measurement of SAR in phantoms simulating the human body. In this study a calibration based on a rectangular waveguide was developed for SAR calibrations at 900 MHz

Improved SAR Image Coregistration Using Pixel-Offset Series

KAUST Repository

Wang, Teng

2014-03-14

Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

Improved SAR Image Coregistration Using Pixel-Offset Series

KAUST Repository

Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

2014-01-01

Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

Directory of Open Access Journals (Sweden)

U. G. Sefercik

2017-09-01

Full Text Available In synthetic aperture radar (SAR technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX and Cosmo-SkyMed (CSK since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM acquisition for urban areas utilizing interferometric SAR (InSAR technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

Magnetic moment distribution in Co-V alloys

International Nuclear Information System (INIS)

Cable, J.W.

1982-01-01

Magnetization and neutron scattering measurements were made on Co-V alloys containing 10, 15, and 20 at.% V to determine the local environment effects on the magnetic moment distribution in this system. The magnetization data agree with earlier results and suggest the presence of some hcp phase in the 10% sample. This was confirmed by the neutron data which showed both fcc and hcp phases in an approximate 4:1 volume ratio for this alloy. The other two samples were single phase fcc but the 15% alloy was disordered while the 20% alloy was ordered in the Cu 3 Au-type structure with the maximum order consistent with the concentration. In this ordered alloy, the excess Co occupies the V sites. These ''wrong sited'' Co atoms have 12 Co nearest neighbors and larger magnetic moments than the ''properly sited'' Co atoms which have an average of 8.8 Co nearest neighbors. The average moments associated with these two types of sites were determined from flipping-ratio measurements on the superlattice and fundamental reflections. The values obtained are 0.28 μ/sub B//Co for the proper-site atoms and 1.3 μ/sub B//Co for the wrong-site atoms. Average moments at the Co and V sites were determined from the diffuse scattering for the 10% and 15% alloys. The results are 1.38 μ/sub B//Co and -0.26 μ/sub B//V for the 10% sample and 1.05 μ/sub B//Co and -0.11 μ/sub B//V for the 15% sample

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

Science.gov (United States)

Xu, Xin; Gui, Rong; Pu, Fangling

2018-01-01

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

Science.gov (United States)

Lilin Guo; Zhenzhong Wang; Cabrerizo, Mercedes; Adjouadi, Malek

2016-08-01

This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule to automate the detection of interictal spikes in electroencephalogram (EEG) data on patients with epilepsy. Encoding is the initial yet essential step for spiking neurons to process EEG patterns. A new encoding method is utilized to convert the EEG signal into spike patterns. The simulation results show that the proposed algorithm identified 69 spikes out of 82 spikes, or 84% detection rate, which is quite high considering the subtleties of interictal spikes and the tediousness of monitoring long EEG records. This CCDS rule is also benchmarked by ReSuMe on the same task.

A Novel 3D Imaging Method for Airborne Downward-Looking Sparse Array SAR Based on Special Squint Model

Directory of Open Access Journals (Sweden)

Xiaozhen Ren

2014-01-01

Full Text Available Three-dimensional (3D imaging technology based on antenna array is one of the most important 3D synthetic aperture radar (SAR high resolution imaging modes. In this paper, a novel 3D imaging method is proposed for airborne down-looking sparse array SAR based on the imaging geometry and the characteristic of echo signal. The key point of the proposed algorithm is the introduction of a special squint model in cross track processing to obtain accurate focusing. In this special squint model, point targets with different cross track positions have different squint angles at the same range resolution cell, which is different from the conventional squint SAR. However, after theory analysis and formulation deduction, the imaging procedure can be processed with the uniform reference function, and the phase compensation factors and algorithm realization procedure are demonstrated in detail. As the method requires only Fourier transform and multiplications and thus avoids interpolations, it is computationally efficient. Simulations with point scatterers are used to validate the method.

Relevant Scatterers Characterization in SAR Images

Science.gov (United States)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

Predictive coding of dynamical variables in balanced spiking networks.

Science.gov (United States)

Boerlin, Martin; Machens, Christian K; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

High-speed railway bridge dynamic measurement based on GB-InSAR technology

Science.gov (United States)

Liu, Miao; Ding, Ke-liang; Liu, Xianglei; Song, Zichao

2015-12-01

It is an important task to evaluate the safety during the life of bridges using the corresponding vibration parameters. With the advantages of non-contact and high accuracy, the new remote measurement technology of GB-InSAR is suitable to make dynamic measurement for bridges to acquire the vibration parameters. Three key technologies, including stepped frequency-continuous wave technique, synthetic aperture radar and interferometric measurement technique, are introduced in this paper. The GB-InSAR is applied for a high-speed railway bridge to measure of dynamic characteristics with the train passing which can be used to analyze the safety of the monitored bridge. The test results shown that it is an reliable non-contact technique for GB-InSAR to acquire the dynamic vibration parameter for the high-speed railway bridges.

Surfing a spike wave down the ventral stream.

Science.gov (United States)

VanRullen, Rufin; Thorpe, Simon J

2002-10-01

Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.

Implementing Signature Neural Networks with Spiking Neurons.

Science.gov (United States)

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

SAR: Stroke Authorship Recognition

KAUST Repository

Shaheen, Sara

2015-10-15

Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

Science.gov (United States)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Crystallization and preliminary X-ray diffraction analysis of Nsp15 from SARS coronavirus

International Nuclear Information System (INIS)

Ricagno, Stéfano; Coutard, Bruno; Grisel, Sacha; Brémond, Nicolas; Dalle, Karen; Tocque, Fabienne; Campanacci, Valérie; Lichière, Julie; Lantez, Violaine; Debarnot, Claire; Cambillau, Christian; Canard, Bruno; Egloff, Marie-Pierre

2006-01-01

Crystals of Nsp15 from the aetiological agent of SARS have been grown at room temperature. Crystals have cubic symmetry and diffract to a maximum resolution of 2.7 Å. The non-structural protein Nsp15 from the aetiological agent of SARS (severe acute respiratory syndrome) has recently been characterized as a uridine-specific endoribonuclease. This enzyme plays an essential role in viral replication and transcription since a mutation in the related H229E human coronavirus nsp15 gene can abolish viral RNA synthesis. SARS full-length Nsp15 (346 amino acids) has been cloned and expressed in Escherichia coli with an N-terminal hexahistidine tag and has been purified to homogeneity. The protein was subsequently crystallized using PEG 8000 or 10 000 as precipitants. Small cubic crystals of the apoenzyme were obtained from 100 nl nanodrops. They belong to space group P4 1 32 or P4 3 32, with unit-cell parameters a = b = c = 166.8 Å. Diffraction data were collected to a maximum resolution of 2.7 Å

Crystallization and preliminary X-ray diffraction analysis of Nsp15 from SARS coronavirus

Energy Technology Data Exchange (ETDEWEB)

Ricagno, Stéfano; Coutard, Bruno; Grisel, Sacha; Brémond, Nicolas; Dalle, Karen; Tocque, Fabienne; Campanacci, Valérie; Lichière, Julie; Lantez, Violaine; Debarnot, Claire; Cambillau, Christian; Canard, Bruno; Egloff, Marie-Pierre, E-mail: marie-pierre.egloff@afmb.univ-mrs.fr [Centre National de la Recherche Scientifique and Universités d’Aix-Marseille I et II, UMR 6098, Architecture et Fonction des Macromolécules Biologiques, Ecole Supérieure d’Ingénieurs de Luminy-Case 925, 163 Avenue de Luminy, 13288 Marseille CEDEX 9 (France)

2006-04-01

Crystals of Nsp15 from the aetiological agent of SARS have been grown at room temperature. Crystals have cubic symmetry and diffract to a maximum resolution of 2.7 Å. The non-structural protein Nsp15 from the aetiological agent of SARS (severe acute respiratory syndrome) has recently been characterized as a uridine-specific endoribonuclease. This enzyme plays an essential role in viral replication and transcription since a mutation in the related H229E human coronavirus nsp15 gene can abolish viral RNA synthesis. SARS full-length Nsp15 (346 amino acids) has been cloned and expressed in Escherichia coli with an N-terminal hexahistidine tag and has been purified to homogeneity. The protein was subsequently crystallized using PEG 8000 or 10 000 as precipitants. Small cubic crystals of the apoenzyme were obtained from 100 nl nanodrops. They belong to space group P4{sub 1}32 or P4{sub 3}32, with unit-cell parameters a = b = c = 166.8 Å. Diffraction data were collected to a maximum resolution of 2.7 Å.

Localized landslide risk assessment with multi pass L band DInSAR analysis

Science.gov (United States)

Yun, HyeWon; Rack Kim, Jung; Lin, Shih-Yuan; Choi, YunSoo

2014-05-01

In terms of data availability and error correction, landslide forecasting by Differential Interferometric SAR (DInSAR) analysis is not easy task. Especially, the landslides by the anthropogenic construction activities frequently occurred in the localized cutting side of mountainous area. In such circumstances, it is difficult to attain sufficient enough accuracy because of the external factors inducing the error component in electromagnetic wave propagation. For instance, the local climate characteristics such as orographic effect and the proximity to water source can produce the significant anomalies in the water vapor distribution and consequently result in the error components of InSAR phase angle measurements. Moreover the high altitude parts of target area cause the stratified tropospheric delay error in DInSAR measurement. The other obstacle in DInSAR observation over the potential landside site is the vegetation canopy which causes the decorrelation of InSAR phase. Thus rather than C band sensor such as ENVISAT, ERS and RADARSAT, DInSAR analysis with L band ALOS PLASAR is more recommendable. Together with the introduction of L band DInSAR analysis, the improved DInSAR technique to cope all above obstacles is necessary. Thus we employed two approaches i.e. StaMPS/MTI (Stanford Method for Persistent Scatterers/Multi-Temporal InSAR, Hopper et al., 2007) which was newly developed for extracting the reliable deformation values through time series analysis and two pass DInSAR with the error term compensation based on the external weather information in this study. Since the water vapor observation from spaceborne radiometer is not feasible by the temporal gap in this case, the quantities from weather Research Forecasting (WRF) with 1 km spatial resolution was used to address the atmospheric phase error in two pass DInSAR analysis. Also it was observed that base DEM offset with time dependent perpendicular baselines of InSAR time series produce a significant error

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

Directory of Open Access Journals (Sweden)

Jan Hahne

2017-05-01

Full Text Available Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

Science.gov (United States)

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Bistatic SAR: Imagery & Image Products.

Energy Technology Data Exchange (ETDEWEB)

Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

2014-10-01

While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

2D co-ordinate transformation based on a spike timing-dependent plasticity learning mechanism.

Science.gov (United States)

Wu, QingXiang; McGinnity, Thomas Martin; Maguire, Liam; Belatreche, Ammar; Glackin, Brendan

2008-11-01

In order to plan accurate motor actions, the brain needs to build an integrated spatial representation associated with visual stimuli and haptic stimuli. Since visual stimuli are represented in retina-centered co-ordinates and haptic stimuli are represented in body-centered co-ordinates, co-ordinate transformations must occur between the retina-centered co-ordinates and body-centered co-ordinates. A spiking neural network (SNN) model, which is trained with spike-timing-dependent-plasticity (STDP), is proposed to perform a 2D co-ordinate transformation of the polar representation of an arm position to a Cartesian representation, to create a virtual image map of a haptic input. Through the visual pathway, a position signal corresponding to the haptic input is used to train the SNN with STDP synapses such that after learning the SNN can perform the co-ordinate transformation to generate a representation of the haptic input with the same co-ordinates as a visual image. The model can be applied to explain co-ordinate transformation in spiking neuron based systems. The principle can be used in artificial intelligent systems to process complex co-ordinate transformations represented by biological stimuli.

Underwater Topography Detection in Coastal Areas Using Fully Polarimetric SAR Data

Directory of Open Access Journals (Sweden)

Xiaolin Bian

2017-06-01

Full Text Available Fully polarimetric synthetic aperture radar (SAR can provide detailed information on scattering mechanisms that could enable the target or structure to be identified. This paper presents a method to detect underwater topography in coastal areas using high resolution fully polarimetric SAR data, while less prior information is required. The method is based on the shoaling and refraction of long surface gravity waves as they propagate shoreward. First, the surface scattering component is obtained by polarization decomposition. Then, wave fields are retrieved from the two-dimensional (2D spectra by the Fast Fourier Transformation (FFT. Finally, shallow water depths are estimated from the dispersion relation. Applicability and effectiveness of the proposed methodology are tested by using C-band fine quad-polarization mode RADARSAT-2 SAR data over the near-shore area of the Hainan province, China. By comparing with the values from an official electronic navigational chart (ENC, the estimated water depths are in good agreement with them. The average relative error of the detected results from the scattering mechanisms based method and single polarization SAR data are 9.73% and 11.53% respectively. The validation results indicate that the scattering mechanisms based methodology is more effective than only using the single polarization SAR data for underwater topography detection, and will inspire further research on underwater topography detection with fully polarimetric SAR data.

Identification of active release planes using ground-based differential InSAR at the Randa rock slope instability, Switzerland

Directory of Open Access Journals (Sweden)

V. Gischig

2009-12-01

Full Text Available Five ground-based differential interferometric synthetic aperture radar (GB-DInSAR surveys were conducted between 2005 and 2007 at the rock slope instability at Randa, Switzerland. Resultant displacement maps revealed, for the first time, the presence of an active basal rupture zone and a lateral release surface daylighting on the exposed 1991 failure scarp. Structures correlated with the boundaries of interferometric displacement domains were confirmed using a helicopter-based LiDAR DTM and oblique aerial photography. Former investigations at the site failed to conclusively detect these active release surfaces essential for kinematic and hazard analysis of the instability, although their existence had been hypothesized. The determination of the basal and lateral release planes also allowed a more accurate estimate of the currently unstable volume of 5.7±1.5 million m³. The displacement patterns reveal that two different kinematic behaviors dominate the instability, i.e. toppling above 2200 m and translational failure below. In the toppling part of the instability the areas with the highest GB-DInSAR displacements correspond to areas of enhanced micro-seismic activity. The observation of only few strongly active discontinuities daylighting on the 1991 failure surface points to a rather uniform movement in the lower portion of the instability, while most of the slip occurs along the basal rupture plane. Comparison of GB-DInSAR displacements with mapped discontinuities revealed correlations between displacement patterns and active structures, although spatial offsets occur as a result of the effective resolution of GB-DInSAR. Similarly, comparisons with measurements from total station surveys generally showed good agreement. Discrepancies arose in several cases due to local movement of blocks, the size of which could not be resolved using GB-DInSAR.

SAR Cross-Ambiguities in SAOCOM-CS Large Baseline Bistatic Configuration

OpenAIRE

Bordoni, Federica; Rodriguez-Cassola, Marc; Younis, Marwan; Prats-Iraola, Pau; Lopez-Dekker, Paco; Krieger, Gerhard

2016-01-01

The evaluation of the ambiguous signal level, the Ambiguity-to-Signal Ratio (ASR), plays a key role in the Synthetic Aperture Radar (SAR) design and performance prediction. In conventional SAR acquisition scenarios, the computation of the ASR is based on the evaluation of the range and azimuth ambiguous contributes. Though appealing for its simplicity, this approach could be inaccurate in case of complex SAR acquisition geometries. In this paper we focus on the ASR performance of the SAOCOM-...

Spike rate and spike timing contributions to coding taste quality information in rat periphery

Directory of Open Access Journals (Sweden)

Vernon eLawhern

2011-05-01

Full Text Available There is emerging evidence that individual sensory neurons in the rodent brain rely on temporal features of the discharge pattern to code differences in taste quality information. In contrast, in-vestigations of individual sensory neurons in the periphery have focused on analysis of spike rate and mostly disregarded spike timing as a taste quality coding mechanism. The purpose of this work was to determine the contribution of spike timing to taste quality coding by rat geniculate ganglion neurons using computational methods that have been applied successfully in other sys-tems. We recorded the discharge patterns of narrowly-tuned and broadly-tuned neurons in the rat geniculate ganglion to representatives of the five basic taste qualities. We used mutual in-formation to determine significant responses and the van Rossum metric to characterize their temporal features. While our findings show that spike timing contributes a significant part of the message, spike rate contributes the largest portion of the message relayed by afferent neurons from rat fungiform taste buds to the brain. Thus, spike rate and spike timing together are more effective than spike rate alone in coding stimulus quality information to a single basic taste in the periphery for both narrowly-tuned specialist and broadly-tuned generalist neurons.

Crop Classification by Polarimetric SAR

DEFF Research Database (Denmark)

Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming

1999-01-01

Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...

Impact of spike train autostructure on probability distribution of joint spike events.

Science.gov (United States)

Pipa, Gordon; Grün, Sonja; van Vreeswijk, Carl

2013-05-01

The discussion whether temporally coordinated spiking activity really exists and whether it is relevant has been heated over the past few years. To investigate this issue, several approaches have been taken to determine whether synchronized events occur significantly above chance, that is, whether they occur more often than expected if the neurons fire independently. Most investigations ignore or destroy the autostructure of the spiking activity of individual cells or assume Poissonian spiking as a model. Such methods that ignore the autostructure can significantly bias the coincidence statistics. Here, we study the influence of the autostructure on the probability distribution of coincident spiking events between tuples of mutually independent non-Poisson renewal processes. In particular, we consider two types of renewal processes that were suggested as appropriate models of experimental spike trains: a gamma and a log-normal process. For a gamma process, we characterize the shape of the distribution analytically with the Fano factor (FFc). In addition, we perform Monte Carlo estimations to derive the full shape of the distribution and the probability for false positives if a different process type is assumed as was actually present. We also determine how manipulations of such spike trains, here dithering, used for the generation of surrogate data change the distribution of coincident events and influence the significance estimation. We find, first, that the width of the coincidence count distribution and its FFc depend critically and in a nontrivial way on the detailed properties of the structure of the spike trains as characterized by the coefficient of variation CV. Second, the dependence of the FFc on the CV is complex and mostly nonmonotonic. Third, spike dithering, even if as small as a fraction of the interspike interval, can falsify the inference on coordinated firing.

AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

P. Fischer

2018-04-01

Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

Science.gov (United States)

An, Quanzhi; Pan, Zongxu; You, Hongjian

2018-01-24

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

Nicotine-Mediated ADP to Spike Transition: Double Spiking in Septal Neurons.

Science.gov (United States)

Kodirov, Sodikdjon A; Wehrmeister, Michael; Colom, Luis

2016-04-01

The majority of neurons in lateral septum (LS) are electrically silent at resting membrane potential. Nicotine transiently excites a subset of neurons and occasionally leads to long lasting bursting activity upon longer applications. We have observed simultaneous changes in frequencies and amplitudes of spontaneous action potentials (AP) in the presence of nicotine. During the prolonged exposure, nicotine increased numbers of spikes within a burst. One of the hallmarks of nicotine effects was the occurrences of double spikes (known also as bursting). Alignment of 51 spontaneous spikes, triggered upon continuous application of nicotine, revealed that the slope of after-depolarizing potential gradually increased (1.4 vs. 3 mV/ms) and neuron fired the second AP, termed as double spiking. A transition from a single AP to double spikes increased the amplitude of after-hyperpolarizing potential. The amplitude of the second (premature) AP was smaller compared to the first one, and this correlation persisted in regard to their duration (half-width). A similar bursting activity in the presence of nicotine, to our knowledge, has not been reported previously in the septal structure in general and in LS in particular.

Polarimetric scattering and SAR information retrieval

CERN Document Server

Jin, Ya-Qiu

2013-01-01

Taking an innovative look at Synthetic Aperture Radar (SAR), this practical reference fully covers new developments in SAR and its various methodologies and enables readers to interpret SAR imagery An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics. It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface. The book includes quantitative app

Genetic characterization of Betacoronavirus lineage C viruses in bats reveals marked sequence divergence in the spike protein of pipistrellus bat coronavirus HKU5 in Japanese pipistrelle: implications for the origin of the novel Middle East respiratory syndrome coronavirus.

Science.gov (United States)

Lau, Susanna K P; Li, Kenneth S M; Tsang, Alan K L; Lam, Carol S F; Ahmed, Shakeel; Chen, Honglin; Chan, Kwok-Hung; Woo, Patrick C Y; Yuen, Kwok-Yung

2013-08-01

While the novel Middle East respiratory syndrome coronavirus (MERS-CoV) is closely related to Tylonycteris bat CoV HKU4 (Ty-BatCoV HKU4) and Pipistrellus bat CoV HKU5 (Pi-BatCoV HKU5) in bats from Hong Kong, and other potential lineage C betacoronaviruses in bats from Africa, Europe, and America, its animal origin remains obscure. To better understand the role of bats in its origin, we examined the molecular epidemiology and evolution of lineage C betacoronaviruses among bats. Ty-BatCoV HKU4 and Pi-BatCoV HKU5 were detected in 29% and 25% of alimentary samples from lesser bamboo bat (Tylonycteris pachypus) and Japanese pipistrelle (Pipistrellus abramus), respectively. Sequencing of their RNA polymerase (RdRp), spike (S), and nucleocapsid (N) genes revealed that MERS-CoV is more closely related to Pi-BatCoV HKU5 in RdRp (92.1% to 92.3% amino acid [aa] identity) but is more closely related to Ty-BatCoV HKU4 in S (66.8% to 67.4% aa identity) and N (71.9% to 72.3% aa identity). Although both viruses were under purifying selection, the S of Pi-BatCoV HKU5 displayed marked sequence polymorphisms and more positively selected sites than that of Ty-BatCoV HKU4, suggesting that Pi-BatCoV HKU5 may generate variants to occupy new ecological niches along with its host in diverse habitats. Molecular clock analysis showed that they diverged from a common ancestor with MERS-CoV at least several centuries ago. Although MERS-CoV may have diverged from potential lineage C betacoronaviruses in European bats more recently, these bat viruses were unlikely to be the direct ancestor of MERS-CoV. Intensive surveillance for lineage C betaCoVs in Pipistrellus and related bats with diverse habitats and other animals in the Middle East may fill the evolutionary gap.

Block adjustment of airborne InSAR based on interferogram phase and POS data

Science.gov (United States)

Yue, Xijuan; Zhao, Yinghui; Han, Chunming; Dou, Changyong

2015-12-01

High-precision surface elevation information in large scale can be obtained efficiently by airborne Interferomatric Synthetic Aperture Radar (InSAR) system, which is recently becoming an important tool to acquire remote sensing data and perform mapping applications in the area where surveying and mapping is difficult to be accomplished by spaceborne satellite or field working. . Based on the study of the three-dimensional (3D) positioning model using interferogram phase and Position and Orientation System (POS) data and block adjustment error model, a block adjustment method to produce seamless wide-area mosaic product generated from airborne InSAR data is proposed in this paper. The effect of 6 parameters, including trajectory and attitude of the aircraft, baseline length and incline angle, slant range, and interferometric phase, on the 3D positioning accuracy is quantitatively analyzed. Using the data acquired in the field campaign conducted in Mianyang county Sichuan province, China in June 2011, a mosaic seamless Digital Elevation Model (DEM) product was generated from 76 images in 4 flight strips by the proposed block adjustment model. The residuals of ground control points (GCPs), the absolute positioning accuracy of check points (CPs) and the relative positioning accuracy of tie points (TPs) both in same and adjacent strips were assessed. The experimental results suggest that the DEM and Digital Orthophoto Map (DOM) product generated by the airborne InSAR data with sparse GCPs can meet mapping accuracy requirement at scale of 1:10 000.

A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

Directory of Open Access Journals (Sweden)

Min Liu

2018-03-01

Full Text Available Sidelobe reduction is a very primary task for synthetic aperture radar (SAR images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.

Phase correction and error estimation in InSAR time series analysis