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- 저자 : S. K. Khare (검색결과 5 건)
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Pond sediment magnetite grains show a distinctive microbial community.
Song, H-K,Sonkaria, S,Khare, V,Dong, K,Lee, H-T,Ahn, S-H,Kim, H-K,Kang, H-J,Lee, S-H,Jung, S P,Adams, J M Springer-Verlag 2015 Microbial ecology Vol.70 No.1
<P>Formation of magnetite in anaerobic sediments is thought to be enhanced by the activities of iron-reducing bacteria. Geobacter has been implicated as playing a major role, as in culture its cells are often associated with extracellular magnetite grains. We studied the bacterial community associated with magnetite grains in sediment of a freshwater pond in South Korea. Magnetite was isolated from the sediment using a magnet. The magnetite-depleted fraction of sediment was also taken for comparison. DNA was extracted from each set of samples, followed by PCR for 16S bacterial ribosomal RNA (rRNA) gene and HiSeq sequencing. The bacterial communities of the magnetite-enriched and magnetite-depleted fractions were significantly different. The enrichment of three abundant operational taxonomic units (OTUs) suggests that they may either be dependent upon the magnetite grain environment or may be playing a role in magnetite formation. The most abundant OTU in magnetite-enriched fractions was Geobacter, bolstering the case that this genus is important in magnetite formation in natural systems. Other major OTUs strongly associated with the magnetite-enriched fraction, rather than the magnetite-depleted fraction, include a Sulfuricella and a novel member of the Betaproteobacteria. The existence of distinct bacterial communities associated with particular mineral grain types may also be an example of niche separation and coexistence in sediments and soils, which cannot usually be detected due to difficulties in separating and concentrating minerals.</P>
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Multicity Seasonal Air Quality Index Forecasting using Soft Computing Techniques
Tikhe, Shruti S.,Khare, K.C.,Londhe, S.N. Techno-Press 2015 Advances in environmental research Vol.4 No.2
Air Quality Index (AQI) is a pointer to broadcast short term air quality. This paper presents one day ahead AQI forecasting on seasonal basis for three major cities in Maharashtra State, India by using Artificial Neural Networks (ANN) and Genetic Programming (GP). The meteorological observations & previous AQI from 2005-2008 are used to predict next day's AQI. It was observed that GP captures the phenomenon better than ANN and could also follow the peak values better than ANN. The overall performance of GP seems better as compared to ANN. Stochastic nature of the input parameters and the possibility of auto-correlation might have introduced time lag and subsequent errors in predictions. Spectral Analysis (SA) was used for characterization of the error introduced. Correlational dependency (serial dependency) was calculated for all 24 models prepared on seasonal basis. Particular lags (k) in all the models were removed by differencing the series, that is converting each i'th element of the series into its difference from the (i-k)"th element. New time series is generated for all seasonal models in synchronization with the original time line & evaluated using ANN and GP. The statistical analysis and comparison of GP and ANN models has been done. We have proposed a promising approach of use of GP coupled with SA for real time prediction of seasonal multicity AQI.
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Spatio-temporal estimation of air quality parameters using linear genetic programming
Tikhe, Shruti S.,Khare, K.C.,Londhe, S.N. Techno-Press 2017 Advances in environmental research Vol.6 No.2
Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.
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Ram Karan,Raj Kumar Mohan Singh,Sanjay Kapoor,S. K. Khare 한국미생물 · 생명공학회 2011 Journal of microbiology and biotechnology Vol.21 No.2
Cloning and characterization of the gene encoding a solvent-tolerant protease from the haloalkaliphilic bacterium Geomicrobium sp. EMB2 are described. Primers designed based on the N-terminal amino acid sequence of the purified EMB2 protease helped in the amplification of a 1,505-bp open reading frame that had a coding potential of a 42.7-kDa polypeptide. The deduced EMB2 protein contained a 35.4-kDa mature protein of 311 residues, with a high proportion of acidic amino acid residues. Phylogenetic analysis placed the EMB2 gene close to a known serine protease from Bacillus clausii KSM-K16. Primary sequence analysis indicated a hydrophobic inclination of the protein; and the 3D structure modeling elucidated a relatively higher percentage of small (glycine, alanine, and valine) and borderline (serine and threonine) hydrophobic residues on its surface. The structure analysis also highlighted enrichment of acidic residues at the cost of basic residues. The study indicated that solvent and salt stabilities in Geomicrobium sp. protease may be accorded to different structural features; that is, the presence of a number of small hydrophobic amino acid residues on the surface and a higher content of acidic amino acid residues, respectively.
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