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Assessment of water quality using multivariate analysis�a case study on the Brahmaputra River, Assam, India
No full textChemical composition of river water is vital to assessment of water quality for irrigation, agriculture and domestic usage. Chemical attributes of riverine water primarily governed by natural weathering of rocks have become overshadowed by increasing range of anthropogenic activities. Progressive pollution of the river waters are critical as rivers in floodplain zones recharge ground water; a vital source of drinking water in India. The degree of impact of the anthropogenic activities within the surface waters of the developing countries has expanded significantly amid the past decades. Hence identification and quantification of natural as well as anthropogenic impact and understanding the source of contaminant is fundamental. In addition continuous monitoring of river water quality is required in order to maintain freshwater assets. The Brahmaputra River is the lifeline of Assam. People residing along its bank directly or indirectly are heavily dependent on the river for their livelihood. Majority of the population in the region is dependent on an agricultural economy. In the present study different multivariate statistical techniques such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) were applied for evaluation of spatial and temporal variations of water quality of the Brahmaputra River for two years (2011�2014) by monitoring nine sampling sites from upstream to downstream along the Assam stretch. The present study highlights the usefulness and need of multivariate statistical assessment of the database in identification of main process that influence the water quality of the river and probable source of contamination.by Pallavi Das and Manish Kuma
All-sky search for short gravitational-wave bursts in the second Advanced LIGO and Advanced Virgo run
No full textWe present the results of a search for short-duration gravitational-wave transients in the data from the second observing run of Advanced LIGO and Advanced Virgo. We search for gravitational-wave transients with a duration of milliseconds to approximately one second in the 32–4096 Hz frequency band with minimal assumptions about the signal properties, thus targeting a wide variety of sources. We also perform a matched-filter search for gravitational-wave transients from cosmic string cusps for which the waveform is well modeled. The unmodeled search detected gravitational waves from several binary black hole mergers which have been identified by previous analyses. No other significant events have been found by either the unmodeled search or the cosmic string search. We thus present the search sensitivities for a variety of signal waveforms and report upper limits on the source rate density as a function of the characteristic frequency of the signal. These upper limits are a factor of 3 lower than the first observing run, with a 50% detection probability for gravitational-wave emissions with energies of ∼10−9 M⊙c2 at 153 Hz. For the search dedicated to cosmic string cusps we consider several loop distribution models, and present updated constraints from the same search done in the first observing run
Synthesis studies and application of porphyrinsand boron dipyrromethenes appended with energy donor groups
No full textby E. K. PraseethaPh.D
