6,121 research outputs found
Analysis of the Early-time Optical Spectra of SN 2011fe in M101
The nearby Type Ia supernova (SN Ia) SN 2011fe in M101 (cz = 241 km s^(–1)) provides a unique opportunity to study the early evolution of a "normal" SN Ia, its compositional structure, and its elusive progenitor system. We present 18 high signal-to-noise spectra of SN 2011fe during its first month beginning 1.2 days post-explosion and with an average cadence of 1.8 days. This gives a clear picture of how various line-forming species are distributed within the outer layers of the ejecta, including that of unburned material (C+O). We follow the evolution of C II absorption features until they diminish near maximum light, showing overlapping regions of burned and unburned material between ejection velocities of 10,000 and 16,000 km s^(–1). This supports the notion that incomplete burning, in addition to progenitor scenarios, is a relevant source of spectroscopic diversity among SNe Ia. The observed evolution of the highly Doppler-shifted O I λ7774 absorption features detected within 5 days post-explosion indicates the presence of O I with expansion velocities from 11,500 to 21,000 km s^(–1). The fact that some O I is present above C II suggests that SN 2011fe may have had an appreciable amount of unburned oxygen within the outer layers of the ejecta
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
The idea of computer vision as the Bayesian inverse problem to computer
graphics has a long history and an appealing elegance, but it has proved
difficult to directly implement. Instead, most vision tasks are approached via
complex bottom-up processing pipelines. Here we show that it is possible to
write short, simple probabilistic graphics programs that define flexible
generative models and to automatically invert them to interpret real-world
images. Generative probabilistic graphics programs consist of a stochastic
scene generator, a renderer based on graphics software, a stochastic likelihood
model linking the renderer's output and the data, and latent variables that
adjust the fidelity of the renderer and the tolerance of the likelihood model.
Representations and algorithms from computer graphics, originally designed to
produce high-quality images, are instead used as the deterministic backbone for
highly approximate and stochastic generative models. This formulation combines
probabilistic programming, computer graphics, and approximate Bayesian
computation, and depends only on general-purpose, automatic inference
techniques. We describe two applications: reading sequences of degraded and
adversarially obscured alphanumeric characters, and inferring 3D road models
from vehicle-mounted camera images. Each of the probabilistic graphics programs
we present relies on under 20 lines of probabilistic code, and supports
accurate, approximately Bayesian inferences about ambiguous real-world images.Comment: The first two authors contributed equally to this wor
Monojet searches for momentum-dependent dark matter interactions
We consider minimal dark matter scenarios featuring momentum-dependent couplings of the dark sector to the Standard Model. We derive constraints from existing LHC searches in the monojet channel, estimate the future LHC sensitivity for an integrated luminosity of 300 fb−1, and compare with models exhibiting conventional momentum-independent interactions with the dark sector. In addition to being well motivated by (composite) pseudo-Goldstone dark matter scenarios, momentum-dependent couplings are interesting as they weaken direct detection constraints. For a specific dark matter mass, the LHC turns out to be sensitive to smaller signal cross-sections in the momentum-dependent case, by virtue of the harder jet transverse-momentum distribution
Investigation of laser ablated ZnO thin films grown with Zn metal target: a structural study
High quality ZnO thin films were gown using the pulsed laser deposition
technique on (0001) AlO substrates in an oxidizing atmosphere, using a
Zn metallic target. We varied the growth conditions such as the deposition
temperature and the oxygen pressure. First, using a battery of techniques such
as x-rays diffraction, Rutherford Backscattering spectroscopy and atomic force
microscopy, we evaluated the structural quality, the stress and the degree of
epitaxy of the films. Second, the relations between the deposition conditions
and the structural properties, that are directly related to the nature of the
thin films, are discussed qualitatively. Finally, a number of issues on how to
get good-quality ZnO films are addressed.Comment: To be published in Jour. Appl. Phys. (15 August 2004
Waste Reduction at the Source and Waste Recycle through Briquetting of the Reduction Charge in the black- ash process
Physical losses of material as flue dust in the oil fired rotary furnaces of black ash process for barite reduction have been arrested using briquetted charge. Similarly fine particles of barium sulphate obtained in the purification of barite could be recycled as a resource by exploiting advantages of catalysis and briquetting techniques
Analysis of DNA curvature distribution in mycobacterial promoters using theoretical models
In this paper, 125 different mycobacterial promoters are analyzed for their DNA curvature distribution using several di- and tri-nucleotide dependent models of DNA curvature. Different models give similar behavior and therefore qualitative validation of the results. Mycobacterial promoters resembling the E. coli σ 70 type have almost 81% (85%) sequences having medium and high curvature profiles using dinucleotide-dependent models. Non-E. coli σ 70 type mycobacterial promoters have comparatively higher percent of low curvature profiles. Very few extended -10 promoters have low curvature profiles. Mycobacterial promoters having AnTm (n+m≥ 3) tract in the upstream region of -35 box and repeated in phase with each other have high curvature profiles. M. smegmatis promoters have high curvature profiles compared to M. tuberculosis promoters
Validated method for estimation of irbesartan in bulk and dosage form by high performance liquid chromatography technique
A simple, specific, accurate and precise new high performance liquid chromatographic method was developed for the estimation of irbesartan in bulk and its developed dosage form. The mobile phase containing acetonitrile: Phosphate buffer pH 3.5 in proportion of 50:50 v/v was employed with flow rate of1.0 ml/min and eluting medium was monitored at 240 nm. The method was validated for linearity, accuracy, precision, limit of detection, limit of quantification and robustness for irbesartan. A linear response was observed in the range of 5- 40μg/ml. Linear regression of absorbance on concentration gave equation y = 101.9x + 195.3 with a regression co-efficient r2 =0.993. The method was validated for different parameters as per the ICH guidelines. The degradation studies were carried out by using the developed method. Thus the method was found to be useful for the determination of irbesartan in bulk as well as for dosage forms
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