13,336 research outputs found
Design and multiplierless implementation of two-channel biorthogonal IIR filter banks with low system delay
An efficient method for the design of low-delay two-channel, perfect reconstruction IIR filter banks is proposed. The design problem is formulated in terms of minimax designs of a general stable IIR filter that can be obtained using semidefinite programming and an FIR filter that can be obtained using the Remez exchange algorithm. A multiplierless implementation on this filter bank is also proposed and investigated.published_or_final_versio
Vaccinia Virus Protein C6 Inhibits Type I IFN Signalling in the Nucleus and Binds to the Transactivation Domain of STAT2.
The type I interferon (IFN) response is a crucial innate immune signalling pathway required for defense against viral infection. Accordingly, the great majority of mammalian viruses possess means to inhibit this important host immune response. Here we show that vaccinia virus (VACV) strain Western Reserve protein C6, is a dual function protein that inhibits the cellular response to type I IFNs in addition to its published function as an inhibitor of IRF-3 activation, thereby restricting type I IFN production from infected cells. Ectopic expression of C6 inhibits the induction of interferon stimulated genes (ISGs) in response to IFNα treatment at both the mRNA and protein level. C6 inhibits the IFNα-induced Janus kinase/signal transducer and activator of transcription (JAK/STAT) signalling pathway at a late stage, downstream of STAT1 and STAT2 phosphorylation, nuclear translocation and binding of the interferon stimulated gene factor 3 (ISGF3) complex to the interferon stimulated response element (ISRE). Mechanistically, C6 associates with the transactivation domain of STAT2 and this might explain how C6 inhibits the type I IFN signalling very late in the pathway. During virus infection C6 reduces ISRE-dependent gene expression despite the presence of the viral protein phosphatase VH1 that dephosphorylates STAT1 and STAT2. The ability of a cytoplasmic replicating virus to dampen the immune response within the nucleus, and the ability of viral immunomodulators such as C6 to inhibit multiple stages of the innate immune response by distinct mechanisms, emphasizes the intricacies of host-pathogen interactions and viral immune evasion.Wellcome-Trust, Lister Institute of Preventive Medicine U
Some triviality results for quasi-Einstein manifolds and Einstein warped products
In this paper we prove a number of triviality results for Einstein warped
products and quasi-Einstein manifolds using different techniques and under
assumptions of various nature. In particular we obtain and exploit gradient
estimates for solutions of weighted Poisson-type equations and adaptations to
the weighted setting of some Liouville-type theorems.Comment: 15 pages, fixed minor mistakes in Section
Microscopic coexistence of superconductivity and antiferromagnetism in underdoped Ba(Fe1-xRux)2As2
We use As nuclear magnetic resonance (NMR) to investigate the local
electronic properties of Ba(FeRu)As ( 0.23). We find
two phase transitions, to antiferromagnetism at 60 K and to
superconductivity at 15 K. Below , our data show that the
system is fully magnetic, with a commensurate antiferromagnetic structure and a
moment of 0.4 /Fe. The spin-lattice relaxation rate is
large in the magnetic state, indicating a high density of itinerant electrons
induced by Ru doping. On cooling below , on the magnetic
sites falls sharply, providing unambiguous evidence for the microscopic
coexistence of antiferromagnetism and superconductivity.Comment: Accepted in Phys. Rev. Let
Silicon-based III-V quantum-dot laser for silicon photonics
Monolithic III-V materials grown on Si is a promising platform for silicon photonics. Here, by
investigating the laser performance of two conventional III-V quantum structures on Si, namely quantumdots and quantum-well, we unambiguously demonstrate the excellence and suitability of quantum-dots
over quantum-well in silicon-based laser structure and reveal the physical mechanisms underneath, which
is attributed to the better tolerance characteristic of quantum-dots for optically detrimental defects. Our
work shows that monolithic III-V quantum-dot lasers on Si are the most promising light source for silicon
photonics technology
Tubular epithelial cells in renal clear cell carcinoma express high RIPK1/3 and show increased susceptibility to TNF receptor 1-induced necroptosis.
We previously reported that renal clear cell carcinoma cells (RCC) express both tumor necrosis factor receptor (TNFR)-1 and -2, but that, in organ culture, a TNF mutein that only engages TNFR1, but not TNFR2, causes extensive cell death. Some RCC died by apoptosis based on detection of cleaved caspase 3 in a minority TUNEL-positive cells but the mechanism of death in the remaining cells was unexplained. Here, we underpin the mechanism of TNFR1-induced cell death in the majority of TUNEL-positive RCC cells, and show that they die by necroptosis. Malignant cells in high-grade tumors displayed threefold to four fold higher expression of both receptor-interacting protein kinase (RIPK)1 and RIPK3 compared with non-tumor kidney tubular epithelium and low-grade tumors, but expression of both enzymes was induced in lower grade tumors in organ culture in response to TNFR1 stimulation. Furthermore, TNFR1 activation induced significant MLKL(Ser358) and Drp1(Ser616) phosphorylation, physical interactions in RCC between RIPK1-RIPK3 and RIPK3-phospho-MLKL(Ser358), and coincidence of phospho-MLKL(ser358) and phospho-Drp1(Ser616) at mitochondria in TUNEL-positive RCC. A caspase inhibitor only partially reduced the extent of cell death following TNFR1 engagement in RCC cells, whereas three inhibitors, each targeting a different step in the necroptotic pathway, were much more protective. Combined inhibition of caspases and necroptosis provided additive protection, implying that different subsets of cells respond differently to TNF-α, the majority dying by necroptosis. We conclude that most high-grade RCC cells express increased amounts of RIPK1 and RIPK3 and are poised to undergo necroptosis in response to TNFR1 signaling.National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre , Kidney Research UK and NIH grant R01-HL36003.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Nature Publishing Group
Ultra-strong Adhesion of Graphene Membranes
As mechanical structures enter the nanoscale regime, the influence of van der
Waals forces increases. Graphene is attractive for nanomechanical systems
because its Young's modulus and strength are both intrinsically high, but the
mechanical behavior of graphene is also strongly influenced by the van der
Waals force. For example, this force clamps graphene samples to substrates, and
also holds together the individual graphene sheets in multilayer samples. Here
we use a pressurized blister test to directly measure the adhesion energy of
graphene sheets with a silicon oxide substrate. We find an adhesion energy of
0.45 \pm 0.02 J/m2 for monolayer graphene and 0.31 \pm 0.03 J/m2 for samples
containing 2-5 graphene sheets. These values are larger than the adhesion
energies measured in typical micromechanical structures and are comparable to
solid/liquid adhesion energies. We attribute this to the extreme flexibility of
graphene, which allows it to conform to the topography of even the smoothest
substrates, thus making its interaction with the substrate more liquid-like
than solid-like.Comment: to appear in Nature Nanotechnolog
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An Overview of the Use of Neural Networks for Data Mining Tasks
In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks
Abnormal Event Detection From Videos Using a Two-Stream Recurrent Variational Autoencoder
IEEE With the massive deployment of distributed video surveillance systems, the automatic detection of abnormal events in video streams has become an urgent need. An abnormal event can be considered as a deviation from the regular scene; however, the distribution of normal and abnormal events is severely imbalanced, since the abnormal events do not frequently occur. To make use of a large number of video surveillance videos of regular scenes, we propose a semi-supervised learning scheme, which only uses the data that contains the ordinary scenes. The proposed model has a two-stream structure that is composed of the appearance and motion streams. For each stream, a recurrent variational autoencoder can model the probabilistic distribution of the normal data in a semi-supervised learning scheme. The appearance and motion features from the two streams can provide complementary information to describe this probabilistic distribution. Comprehensive experiments validate the effectiveness of our proposed scheme on several public benchmark datasets which include the Avenue, the Ped1, the Ped2, the Subway-entry, and the Subway-exit
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