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- Rao, P. S. P., et al.
(author)
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Sources of chemical species in rainwater during monsoon and non-monsoonal periods over two mega cities in India and dominant source region of secondary aerosols
- 2016
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In: Atmospheric Environment. - : Elsevier BV. - 1352-2310 .- 1873-2844. ; 146, s. 90-99
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Journal article (peer-reviewed)abstract
- Samples of rainwater (RW) were collected to characterize the chemistry and sources in two representative megacities at Pune (Southwest) and Delhi (Northern) India from 2011 to 2014 across two seasons: monsoon (MN) and non-monsoon (NMN). Collected RW samples were analyzed for major chemical constituents (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Ca2+, and Mg2+), pH and conductivity. In addition, bicarbonate (HCO3-) was also estimated. The mean pH values of the RW were >6 at Pune and <6 at Delhi and 4% and 26% were acidic, respectively. The mean sum of all measured ionic species in Pune and Delhi was 304.7 and 536.4 mu ep/l, respectively, indicating that significant atmospheric pollution effects in these Indian mega cities. Both the Ca2+ and SO42- were the dominant ions, accounting for 43% (Pune) and 54% (Delhi) of the total ions. The sum of measured ions during the NMN period was greater than the NM period by a factor of 1.5 for Pune (278.4: NM and 412.1: NMN mu eq/l) and a factor of about 2.5 for Delhi (406 and 1037.7 mu eq/l). The contributions of SO42- and NO3- to the RW acidity were similar to 40% and 60%, respectively, at Pune and correspondingly, 36% and 64% at Delhi. The concentrations of secondary aerosols (SO42- and NO3-) were higher by a factor of two and three when the air masses were transported to Pune from the continental side. At Delhi, the concentrations of SO42-, NO3-, Ca2+, and Mg2+ were significantly higher when the air masses arrive from Punjab, Haryana, and Pakistan indicating the greater atmospheric pollution over the Indo-Gangetic Plain. Positive matrix factorization was applied to the source apportionment of the deposition fluxes of these ions. Three factors were obtained for Pune and four for Delhi. The sources at Pune were secondary aerosols from fossil fuel combustion, soil dust, and marine, whereas, at Delhi, the sources were soil, fossil fuel combustion, biomass burning, and industrial chlorine.
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- Yadav, A., et al.
(author)
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Groundwater hydrochemistry of rajnandgaon district, chhattisgarh, central india
- 2020
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In: Groundwater for Sustainable Development. - : Elsevier. - 2352-801X. ; 11
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Journal article (peer-reviewed)abstract
- The spreading of fluorosis diseases in Central India related to high concentrations of fluoride ion (F−) is a cause of major concern. In this work, the hydrochemistry of the aquifers related to Seonath River, in Rajnandgaon district, Chhattisgarh state, India, has been studied, focusing on the presence and sources of F−. Hydrochemical parameters were analyzed in the post-monsoon season in 160 wells located in nine tehsils, finding F− concentrations ranging from 0.6 to 18.5 mg L−1. Seasonal variations were also studied in Chhuikhadan tehsil, in which the highest F− values were registered, finding a noticeable enrichment in the pre-monsoon months. In many locations of the district, F− concentrations exceeded the recommended value of 1.5 mg L−1, which have led to the appearance of several health issues. Multidimensional analysis statistical methods were adopted to investigate the sources of F−, and the mineralization of bedrock elements into the groundwater was observed to be the primary source.
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- Calinon, S., et al.
(author)
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Multi-optima exploration with adaptive Gaussian mixture model
- 2012
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In: Development and Learning and Epigenetic Robotics (ICDL), 2012 IEEE International Conference on. - : IEEE. - 9781467349635 ; , s. 6400808-
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Conference paper (peer-reviewed)abstract
- In learning by exploration problems such as reinforcement learning (RL), direct policy search, stochastic optimization or evolutionary computation, the goal of an agent is to maximize some form of reward function (or minimize a cost function). Often, these algorithms are designed to find a single policy solution. We address the problem of representing the space of control policy solutions by considering exploration as a density estimation problem. Such representation provides additional information such as shape and curvature of local peaks that can be exploited to analyze the discovered solutions and guide the exploration. We show that the search process can easily be generalized to multi-peaked distributions by employing a Gaussian mixture model (GMM) with an adaptive number of components. The GMM has a dual role: representing the space of possible control policies, and guiding the exploration of new policies. A variation of expectation-maximization (EM) applied to reward-weighted policy parameters is presented to model the space of possible solutions, as if this space was a probability distribution. The approach is tested in a dart game experiment formulated as a black-box optimization problem, where the agent's throwing capability increases while it chases for the best strategy to play the game. This experiment is used to study how the proposed approach can exploit new promising solution alternatives in the search process, when the optimality criterion slowly drifts over time. The results show that the proposed multi-optima search approach can anticipate such changes by exploiting promising candidates to smoothly adapt to the change of global optimum.
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- Ejaz, Syeda Abida, et al.
(author)
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In-silico Investigations of quinine and quinidine as potential Inhibitors of AKR1B1 and AKR1B10: Functional and structural characterization
- 2022
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In: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 17:10
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Journal article (peer-reviewed)abstract
- The aberrant expression of aldo keto reductases (AKR1B1 & AKR1B10) has been extensively studied in different types of cancer especially the colon cancer but a very few studies have yet been reported regarding the discovery of inhibitors for the treatment of colon cancer by targeting these isozymes. Therefore, there is a need of selective inhibitors of both targets for the eradication of colon cancer. Currently, the study is focused on the exploration of two quinolone compounds i.e., (S)-(6-Methoxyquinolin-4-yl)[(1S,2R,4S,5R)-5-vinylquinuclidin-2-yl]methanol (Quinidine) and (R)-(6-Methoxyquinolin-4-yl)[(1S,2S,4S,5R)-5-vinylquinuclidin-2-yl]methanol (Quinine) as the potential inhibitors of AKR1B1 and AKR1B10 via detailed in-silico approach. The structural properties including vibrational frequencies, dipole moment, polarizability and the optimization energies were estimated using density functional theory (DFT) calculations; where both compounds were found chemically reactive. After that, the optimized structures were used for the molecular docking studies and here quinidine was found more selective towards AKR1B1 and quinine exhibited maximum inhibition of AKR1B10. The results of molecular docking studies were validated by molecular dynamics simulations which provided the deep insight of stability of protein ligand complex. At the end, the ADMET properties were determined to demonstrate the druglikeness properties of both selected compounds. These findings suggested further exploration of both compounds at molecular level using different in-vivo and in-vitro approaches that will lead to the designing of potential inhibitor of AKR1B1/AKR1B10 for curing colon cancer and related malignancies.
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