890 research outputs found
Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction
Estimating uncertainty of camera parameters computed in Structure from Motion
(SfM) is an important tool for evaluating the quality of the reconstruction and
guiding the reconstruction process. Yet, the quality of the estimated
parameters of large reconstructions has been rarely evaluated due to the
computational challenges. We present a new algorithm which employs the sparsity
of the uncertainty propagation and speeds the computation up about ten times
\wrt previous approaches. Our computation is accurate and does not use any
approximations. We can compute uncertainties of thousands of cameras in tens of
seconds on a standard PC. We also demonstrate that our approach can be
effectively used for reconstructions of any size by applying it to smaller
sub-reconstructions.Comment: ECCV 201
30 inch Roll-Based Production of High-Quality Graphene Films for Flexible Transparent Electrodes
We report that 30-inch scale multiple roll-to-roll transfer and wet chemical
doping considerably enhance the electrical properties of the graphene films
grown on roll-type Cu substrates by chemical vapor deposition. The resulting
graphene films shows a sheet resistance as low as ~30 Ohm/sq at ~90 %
transparency which is superior to commercial transparent electrodes such as
indium tin oxides (ITO). The monolayer of graphene shows sheet resistances as
low as ~125 Ohm/sq with 97.4% optical transmittance and half-integer quantum
Hall effect, indicating the high-quality of these graphene films. As a
practical application, we also fabricated a touch screen panel device based on
the graphene transparent electrodes, showing extraordinary mechanical and
electrical performances
Porcine FcγRIIb Mediates Enhancement of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) Infection
Antibody-dependent enhancement (ADE) of virus infection caused by the uptake of virus-antibody complexes by FcγRs is a significant obstacle to the development of effective vaccines to control certain human and animal viral diseases. The activation FcγRs, including FcγRI and FcγRIIa have been shown to mediate ADE infection of virus. In the present paper, we showed that pocine FcγRIIb, an inhibitory FcγR, mediates ADE of PRRSV infection. Stable Marc-145 cell lines expressing poFcγRIIb (Marc-poFcγRII) were established. The relative yield of progeny virus was significantly increased in the presence of sub-neutralization anti-PRRSV antibody. The Fab fragment and normal porcine sera had no effect. Anti-poFcγRII antibody inhibited the enhancement of infection when cells were infected in the presence of anti-PRRSV antibody, but not when cells were infected in the absence of antibody. These results indicate that enhancement of infection in these cells by anti-PRRSV virus antibody is FcγRII-mediated. Identification of the inhibitory FcγR mediating ADE infection should expand our understanding of the mechanisms of pathogenesis for a broad range of infectious diseases and may open many approaches for improvements to the treatment and prevention of such diseases
Pharmacological levels of withaferin A (Withania somnifera) trigger clinically relevant anticancer effects specific to triple negative breast cancer cells
Withaferin A (WA) isolated from Withania somnifera (Ashwagandha) has recently become an attractive phytochemical under investigation in various preclinical studies for treatment of different cancer types. In the present study, a comparative pathway-based transcriptome analysis was applied in epithelial-like MCF-7 and triple negative mesenchymal MDA-MB-231 breast cancer cells exposed to different concentrations of WA which can be detected systemically in in vivo experiments. Whereas WA treatment demonstrated attenuation of multiple cancer hallmarks, the withanolide analogue Withanone (WN) did not exert any of the described effects at comparable concentrations. Pathway enrichment analysis revealed that WA targets specific cancer processes related to cell death, cell cycle and proliferation, which could be functionally validated by flow cytometry and real-time cell proliferation assays. WA also strongly decreased MDA-MB-231 invasion as determined by single-cell collagen invasion assay. This was further supported by decreased gene expression of extracellular matrix-degrading proteases (uPA, PLAT, ADAM8), cell adhesion molecules (integrins, laminins), pro-inflammatory mediators of the metastasis-promoting tumor microenvironment (TNFSF12, IL6, ANGPTL2, CSF1R) and concomitant increased expression of the validated breast cancer metastasis suppressor gene (BRMS1). In line with the transcriptional changes, nanomolar concentrations of WA significantly decreased protein levels and corresponding activity of uPA in MDA-MB-231 cell supernatant, further supporting its anti-metastatic properties. Finally, hierarchical clustering analysis of 84 chromatin writer-reader-eraser enzymes revealed that WA treatment of invasive mesenchymal MDA-MB-231 cells reprogrammed their transcription levels more similarly towards the pattern observed in non-invasive MCF-7 cells. In conclusion, taking into account that sub-cytotoxic concentrations of WA target multiple metastatic effectors in therapy-resistant triple negative breast cancer, WA-based therapeutic strategies targeting the uPA pathway hold promise for further (pre)clinical development to defeat aggressive metastatic breast cancer
AAV2-Mediated Combined Subretinal Delivery of IFN-α and IL-4 Reduces the Severity of Experimental Autoimmune Uveoretinitis
We previously showed that adeno-associated virus 2 (AAV2) mediated subretinal delivery of human interferon-alpha (IFN-α) could effectively inhibit experimental autoimmune uveoretinitis (EAU). In this study we investigated whether subretinal injection of both AVV2.IFN-α and AAV2.IL-4 had a stronger inhibition on EAU activity. B10RIII mice were subretinally injected with AAV2.IFN-α alone (1.5×107 vg), AAV2.IL-4 alone (3.55×107 vg), and AAV2.IFN-α combined with AAV2.IL-4. PBS, AAV2 vector encoding green fluorescent protein (AAV2.GFP) (5×107 vg) was subretinally injected as a control. IFN-α and IL-4 were effectively expressed in the eyes from three weeks to three months following subretinal injection of AAV2 vectors either alone or following combined administration and significantly attenuated EAU activity clinically and histopathologically. AAV2.IL-4 showed a better therapeutic effect as compared to AAV2.IFN-α. The combination of AAV2.IL-4 and AAV2.IFN-α was not significantly different as compared to AAV2.IL-4 alone. There was no difference concerning DTH (delayed-type hypersensitivity) reaction, lymphocyte proliferation and IL-17 production among the investigated treatment groups, suggesting that local retinal gene delivery did not affect the systemic immune response
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds
Humans can robustly recognize and localize objects by integrating visual and
auditory cues. While machines are able to do the same now with images, less
work has been done with sounds. This work develops an approach for dense
semantic labelling of sound-making objects, purely based on binaural sounds. We
propose a novel sensor setup and record a new audio-visual dataset of street
scenes with eight professional binaural microphones and a 360 degree camera.
The co-existence of visual and audio cues is leveraged for supervision
transfer. In particular, we employ a cross-modal distillation framework that
consists of a vision `teacher' method and a sound `student' method -- the
student method is trained to generate the same results as the teacher method.
This way, the auditory system can be trained without using human annotations.
We also propose two auxiliary tasks namely, a) a novel task on Spatial Sound
Super-resolution to increase the spatial resolution of sounds, and b) dense
depth prediction of the scene. We then formulate the three tasks into one
end-to-end trainable multi-tasking network aiming to boost the overall
performance. Experimental results on the dataset show that 1) our method
achieves promising results for semantic prediction and the two auxiliary tasks;
and 2) the three tasks are mutually beneficial -- training them together
achieves the best performance and 3) the number and orientations of microphones
are both important. The data and code will be released to facilitate the
research in this new direction.Comment: Project page:
https://www.trace.ethz.ch/publications/2020/sound_perception/index.htm
Insight into glucocorticoid receptor signalling through interactome model analysis
Glucocorticoid hormones (GCs) are used to treat a variety of diseases because of their potent anti-inflammatory effect and their ability to induce apoptosis in lymphoid malignancies through the glucocorticoid receptor (GR). Despite ongoing research, high glucocorticoid efficacy and widespread usage in medicine, resistance, disease relapse and toxicity remain factors that need addressing. Understanding the mechanisms of glucocorticoid signalling and how resistance may arise is highly important towards improving therapy. To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean model of the glucocorticoid receptor protein interaction network that encapsulates functional relationships between the GR, its target genes or genes that target GR, and the interactions between the genes that interact with the GR. This model named GEB052 consists of 52 nodes representing genes or proteins, the model input (GC) and model outputs (cell death and inflammation), connected by 241 logical interactions of activation or inhibition. 323 changes in the relationships between model constituents following in silico knockouts were uncovered, and steady-state analysis followed by cell-based microarray genome-wide model validation led to an average of 57% correct predictions, which was taken further by assessment of model predictions against patient microarray data. Lastly, semi-quantitative model analysis via microarray data superimposed onto the model with a score flow algorithm has also been performed, which demonstrated significantly higher correct prediction ratios (average of 80%), and the model has been assessed as a predictive clinical tool using published patient microarray data. In summary we present an in silico simulation of the glucocorticoid receptor interaction network, linked to downstream biological processes that can be analysed to uncover relationships between GR and its interactants. Ultimately the model provides a platform for future development both by directing laboratory research and allowing for incorporation of further components, encapsulating more interactions/genes involved in glucocorticoid receptor signalling
X-ray emission from isolated neutron stars
X-ray emission is a common feature of all varieties of isolated neutron stars
(INS) and, thanks to the advent of sensitive instruments with good
spectroscopic, timing, and imaging capabilities, X-ray observations have become
an essential tool in the study of these objects. Non-thermal X-rays from young,
energetic radio pulsars have been detected since the beginning of X-ray
astronomy, and the long-sought thermal emission from cooling neutron star's
surfaces can now be studied in detail in many pulsars spanning different ages,
magnetic fields, and, possibly, surface compositions. In addition, other
different manifestations of INS have been discovered with X-ray observations.
These new classes of high-energy sources, comprising the nearby X-ray Dim
Isolated Neutron Stars, the Central Compact Objects in supernova remnants, the
Anomalous X-ray Pulsars, and the Soft Gamma-ray Repeaters, now add up to
several tens of confirmed members, plus many candidates, and allow us to study
a variety of phenomena unobservable in "standard'' radio pulsars.Comment: Chapter to be published in the book of proceedings of the 1st Sant
Cugat Forum on Astrophysics, "ICREA Workshop on the high-energy emission from
pulsars and their systems", held in April, 201
Circular Permutation of Red Fluorescent Proteins
Circular permutation of fluorescent proteins provides a substrate for the design of molecular sensors. Here we describe a systematic exploration of permutation sites for mCherry and mKate using a tandem fusion template approach. Circular permutants retaining more than 60% (mCherry) and 90% (mKate) brightness of the parent molecules are reported, as well as a quantitative evaluation of the fluorescence from neighboring mutations. Truncations of circular permutants indicated essential N- and C- terminal segments and substantial flexibility in the use of these molecules. Structural evaluation of two cp-mKate variants indicated no major conformational changes from the previously reported wild-type structure, and cis conformation of the chromophores. Four cp-mKates were identified with over 80% of native fluorescence, providing important new building blocks for sensor and complementation experiments
Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set
We report a measurement of the bottom-strange meson mixing phase \beta_s
using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays
in which the quark-flavor content of the bottom-strange meson is identified at
production. This measurement uses the full data set of proton-antiproton
collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment
at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity.
We report confidence regions in the two-dimensional space of \beta_s and the
B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2,
-1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in
agreement with the standard model expectation. Assuming the standard model
value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +-
0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +-
0.009 (syst) ps, which are consistent and competitive with determinations by
other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012
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