226 research outputs found
Geochemical characteristics of charnockite and high grade gneisses from Southern Peninsular Shield and their significance in crustal evolution
Presented here are the results of detailed investigations encompassing externsive structural mapping in the charnockite-high grade gneiss terrain of North Arcot district and the type area in Pallavaram in Tamil Nadu supported by petrography, mineral chemistry, major, minor and REE distribution patterns in various lithounits. This has helped in understanding the evolutionary history of the southern peninsular shield. A possible tectonic model is also suggested. The results of these studies are compared with similar rock types from parts of Andhra Pradesh, Kerala, Sri Lanka, Lapland and Nigeria which has brought about a well defined correlation in geochemical characteristics. The area investigated has an interbanded sequence of thick pile of charnockite and a supracrustal succession of shelf type sediments, layered igneous complex, basic and ultrabasic rocks involved in a complex structural, tectonic, igneous and metamorphic events
Effects of Formaldehyde Fumigation and Fytolan Drench on VAM fungi and nodulation in some Leguminous forest Tree Seedlings in India
Seedlings of 12 legume tree species (Acacia caesia, A. catechu, A. farnesiana, A. holosericea, A.
leucocephala, A. nilotica, Albizia lebbeck, Dichrostachys cinerea, Leucaena latisiliqua, Prosopis
cineraria, Dalbergia latifolia and Pterocarpus marsupium) were raised informaldehyde-fumigatedf Fytol and renched
beds in a nursery. Seedlings in the formaldehyde fumigated beds had stunted growth and were chlorotic; had
poor VAM root colonization (18-25.3%) and spore density (3.1 - 10.6 g. soil-1
) and lower nodule number (3 - 8
plant-1
) and nodular biomass (100 - 870 mg plant-1
); the total biomass (15.5 - 72 g plant-1
) and field survival
rate (31.2 - 40.4%) of the seedlings were very low. The mycorrhizal species isolated were Acaulospora
bireticulata, Glomus fasciculatum and G. geosporum. In contrast, seedlings form Fytolan-drenched beds
showed normal growth, enhanced biomass (18 - 83.21g plant-1
) and higher field survival rate (71 - 86%); intense
VAM root colonization (53.4-100%) and higher spore density (36 - 82.8 g soil-1
) and higher module number (7.4
- 17.6 plant-1
) and nodular biomass (195 - 950 mg plant ) compared with the control seedlings. Roots of these
plants exhibited extensively developed arbuscular and vesicular structures. Ofthe seven VAMF species recordedfrom
the rhizosphere soils of control and Fytolan-drenched beds, A. bireticulata, G. fasciculatum and G. geosporum
were the dominant species. The differences between treatments were statistically significant (P < 0.05)
Sparse Signal Models for Data Augmentation in Deep Learning ATR
Automatic Target Recognition (ATR) algorithms classify a given Synthetic
Aperture Radar (SAR) image into one of the known target classes using a set of
training images available for each class. Recently, learning methods have shown
to achieve state-of-the-art classification accuracy if abundant training data
is available, sampled uniformly over the classes, and their poses. In this
paper, we consider the task of ATR with a limited set of training images. We
propose a data augmentation approach to incorporate domain knowledge and
improve the generalization power of a data-intensive learning algorithm, such
as a Convolutional neural network (CNN). The proposed data augmentation method
employs a limited persistence sparse modeling approach, capitalizing on
commonly observed characteristics of wide-angle synthetic aperture radar (SAR)
imagery. Specifically, we exploit the sparsity of the scattering centers in the
spatial domain and the smoothly-varying structure of the scattering
coefficients in the azimuthal domain to solve the ill-posed problem of
over-parametrized model fitting. Using this estimated model, we synthesize new
images at poses and sub-pixel translations not available in the given data to
augment CNN's training data. The experimental results show that for the
training data starved region, the proposed method provides a significant gain
in the resulting ATR algorithm's generalization performance.Comment: 12 pages, 5 figures, to be submitted to IEEE Transactions on
Geoscience and Remote Sensin
Real-time observation of the optical Sagnac effect in ultrafast bidirectional fibre lasers
The optical Sagnac effect sets fundamentals of the operating principle for ring laser and fiber optic gyroscopes, which are preferred instruments for inertial guidance systems, seismology, and geodesy. Operating at both high bias stability and angular velocity resolutions demands special precautions like dithering or multimode operation to eliminate frequency lock-in or similar effects introduced due to synchronization of counterpropagating channels. Recently, to circumvent these limitations, ultrashort pulsed radiation was suggested to supersede conventional continuous wave operation. Despite the ultrafast nature of ultrashort pulse generation, the interrogation of the Sagnac effect relies on highly averaging measurement methods. Here, we demonstrate the novel approach to the optical Sagnac effect visualization by applying real-time spatiooral intensity processing and time-resolved spectral domain measurements of ultrashort pulse dynamics in rotating the bidirectional ring fiber laser cavity. Our results reveal the high potential of application of novel methods of optical Sagnac effect measurements, allowing enhancement of rotation sensitivity and resolution by several orders of magnitude
Influence of the generated power, measurement bandwidth, and noise level on intensity statistics of a quasi-CW Raman fiber laser
In the present paper we numerically study instrumental impact on statistical properties of quasi-CW Raman fiber laser using a simple model of multimode laser radiation. Effects, that have the most influence, are limited electrical bandwidth of measurement equipment and noise. To check this influence, we developed a simple model of the multimode quasi- CW generation with exponential statistics (i.e. uncorrelated modes). We found that the area near zero intensity in probability density function (PDF) is strongly affected by both factors, for example both lead to formation of a negative wing of intensity distribution. But far wing slope of PDF is not affected by noise and, for moderate mismatch between optical and electrical bandwidth, is only slightly affected by bandwidth limitation. The generation spectrum often becomes broader at higher power in experiments, so the spectral/electrical bandwidth mismatch factor increases over the power that can lead to artificial dependence of the PDF slope over the power. It was also found that both effects influence the ACF background level: noise impact decreases it, while limited bandwidth leads to its increase
Real-time intensity domain characterization of fibre lasers using spatio-temporal dynamics
Fibre lasers are light sources that are synonymous with stability. They can give rise to highly coherent continuous-wave radiation, or a stable train of mode locked pulses with well-defined characteristics. However, they can also exhibit an exceedingly diverse range of nonlinear operational regimes spanning a multi-dimensional parameter space. The complex nature of the dynamics poses significant challenges in the theoretical and experimental studies of such systems. Here, we demonstrate how the real-time experimental methodology of spatio-temporal dynamics can be used to unambiguously identify and discern between such highly complex lasing regimes. This two-dimensional representation of laser intensity allows the identification and tracking of individual features embedded in the radiation as they make round-trip circulations inside the cavity. The salient features of this methodology are highlighted by its application to the case of Raman fibre lasers and a partially mode locked ring fibre laser operating in the normal dispersion regime
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