1,061 research outputs found
Adaptive Edge-Oriented Shot Boundary Detection
We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included
Primordial magnetic fields and the HI signal from the epoch of reionization
The implication of primordial magnetic-field-induced structure formation for
the HI signal from the epoch of reionization is studied. Using semi-analytic
models, we compute both the density and ionization inhomogeneities in this
scenario. We show that: (a) The global HI signal can only be seen in emission,
unlike in the standard CDM models, (b) the density perturbations
induced by primordial fields, leave distinctive signatures of the magnetic
field Jeans' length on the HI two-point correlation function, (c) the length
scale of ionization inhomogeneities is \la 1 \rm Mpc. We find that the peak
expected signal (two-point correlation function) is in
the range of scales for magnetic field strength in the
range . We also discuss the
detectability of the HI signal. The angular resolution of the on-going and
planned radio interferometers allows one to probe only the largest magnetic
field strengths that we consider. They have the sensitivity to detect the
magnetic field-induced features. We show that thefuture SKA has both the
angular resolution and the sensitivity to detect the magnetic field-induced
signal in the entire range of magnetic field values we consider, in an
integration time of one week.Comment: 19 pages, 5 figures, to appear in JCA
Microwave Background Signals from Tangled Magnetic Fields
An inhomogeneous cosmological magnetic field will create Alfven-wave modes
that induce a small rotational velocity perturbation on the last scattering
surface of the microwave background radiation. The Alfven-wave mode survives
Silk damping on much smaller scales than the compressional modes. This, in
combination with its rotational nature, ensures that there will be no sharp
cut-off in anisotropy on arc-minute scales. We estimate that a magnetic field
which redshifts to a present value of Gauss produces
temperature anisotropies at the 10 micro Kelvin level at and below 10 arc-min
scales. A tangled magnetic field, which is large enough to influence the
formation of large scale structure is therefore potentially detectable by
future observations.Comment: 5 pages, Revtex, no figure
Structural characterization, antioxidant and anti-uropathogenic potential of biogenic silver nanoparticles using brown seaweed Turbinaria ornata
Alternative treatment strategies for urinary tract infections (UTIs) are becoming more necessary due to increasing drug resistance patterns in uropathogens. Nanoparticle-based therapeutics is emerging as a way to treat UTIs. In the present study, using Turbinaria ornata extract, silver nanoparticles (AgNPs) were synthesized, characterized, and their anti-uropathogenic activity was evaluated. The stability and formation of synthesized To-AgNPs were confirmed by UV-visible spectroscopy, FTIR, XRD, SEM, and DLS. An FTIR spectrum confirmed the presence of seaweed functional groups in To-AgNPs, a XRD analysis confirmed their crystalline nature, and SEM imaging confirmed their spherical nature with an average size of 73.98 nm with diameters ranging from 64.67 to 81.28 nm. This was confirmed by TEM results. DLS determined that the cumulant hydrodynamic diameter of To-AgNPs was 128.3 nm with a PdI of 0.313 and the zeta potential value were found to be –63.3 mV which indicates the To-AgNPs are negatively charged and more stable. DPPH assays were used to assess the antioxidant activity of biosynthesized To-AgNPs, while an agar well diffusion method was used to test the antibacterial activity against uropathogens, including Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Enterococcus faecalis, and Klebsiella pneumoniae. The To-AgNPs showed the highest susceptibility to S. aureus (15.75 ± 0.35 mm) and E. coli (15 ± 0.7 mm) with MIC values of 0.0625 and 0.125 mg/ml, respectively in macro broth dilution method and observed considerable membrane damage under CLSM and SEM. To-AgNPs displayed stronger antioxidant and antimicrobial activity, suggesting they may be developed as a new class of antimicrobial agents for treating UTIs
Constraints on Variant Axion Models
A particular class of variant axion models with two higgs doublets and a
singlet is studied. In these models the axion couples either to the -quark
or -quark or both, but not to , , , or . When the axion couples
to only one quark the models possess the desirable feature of having no domain
wall problem, which makes them viable candidates for a cosmological axion
string scenario. We calculate the axion couplings to leptons, photons and
nucleons, and the astrophysical constraints on the axion decay constant
are investigated and compared to the DFSZ axion model. We find that the most
restrictive lower bound on , that from SN1987a, is lowered by up to a
factor of about 30, depending on the model and also the ratio of the vacuum
expectation values of the higgs doublets. For scenarios with axionic strings,
the allowed window for in the quark model can be more than two orders
of magnitude. For inflationary scenarios, the cosmological upper bound on
, where is the QCD anomaly factor, is unaffected: however, the
variant models have either 3 or 6 times smaller than the DFSZ model.Comment: 21pp RevTeX, 1 eps fig, uses graphics style, typo corrected, and
corrected file sent this time. To appear in Physical Review
COVID-19: molecular pathophysiology, genetic evolution and prospective therapeutics—a review
The Covid-19 pandemic is highly contagious and has spread rapidly across the globe. To date there have been no specific treatment options available for this life-threatening disease. During this medical emergency, target-based drug repositioning/repurposing with a continuous monitoring and recording of results is an effective method for the treatment and drug discovery. This review summarizes the recent findings on COVID-19, its genomic organization, molecular evolution through phylogenetic analysis and has recapitulated the drug targets by analyzing the viral molecular machinery as drug targets and repurposing of most frequently used drugs worldwide and their therapeutic applications in COVID-19. Data from solidarity trials have shown that the treatment with Chloroquine, hydroxychloroquine and lopinavir-ritonavir had no effect in reducing the mortality rate and also had adverse side effects. Remdesivir, Favipiravir and Ribavirin might be a safer therapeutic option for COVID-19. Recent clinical trial has revealed that dexamethasone and convalescent plasma treatment can reduce mortality in patients with severe forms of COVID-19
Reconstructing cell cycle and disease progression using deep learning
We show that deep convolutional neural networks combined with nonlinear dimension reduction enable reconstructing biological processes based on raw image data. We demonstrate this by reconstructing the cell cycle of Jurkat cells and disease progression in diabetic retinopathy. In further analysis of Jurkat cells, we detect and separate a subpopulation of dead cells in an unsupervised manner and, in classifying discrete cell cycle stages, we reach a sixfold reduction in error rate compared to a recent approach based on boosting on image features. In contrast to previous methods, deep learning based predictions are fast enough for on-the-fly analysis in an imaging flow cytometer
Observation of the Dynamic Beta Effect at CESR with CLEO
Using the silicon strip detector of the CLEO experiment operating at the
Cornell Electron-positron Storage Ring (CESR), we have observed that the
horizontal size of the luminous region decreases in the presence of the
beam-beam interaction from what is expected without the beam-beam interaction.
The dependence on the bunch current agrees with the prediction of the dynamic
beta effect. This is the first direct observation of the effect.Comment: 9 page uuencoded postscript file, postscritp file also available
through http://w4.lns.cornell.edu/public/CLNS, submitted to Phys. Rev.
- …