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( Renganathan Rajkumar ),( Jayappriyan Kothilmozhian Ranishree ),( Rengasamy Ramasamy ) 한국미생물 · 생명공학회 2011 Journal of microbiology and biotechnology Vol.21 No.6
A commercially important alkaline protease, produced by Bacillus sp. RRM1 isolated from the red seaweed Kappaphycus alvarezii (Doty) Doty ex Silva, was first recognized and characterized in the present study. Identification of the isolated bacterium was done using both biochemical characterization as well as 16S rRNA gene sequencing. The bacterial strain, Bacillus sp. RRM1, produced a high level of protease using easily available, inexpensive agricultural residues solid-state fermentation (SSF). Among them, wheat bran was found to be the best substrate. Influences of process parameters such as moistening agents, moisture level, temperature, inoculum concentration, and co-carbon and co-nitrogen sources on the fermentation were also evaluated. Under optimized conditions, maximum protease production (i.e., 2081 U/g) was obtained from wheat bran, which is about 2-fold greater than the initial conditions. The protease enzyme was stable over a temperature range of 30-60oC and pH 6-12, with maximum activity at 50oC and pH 9.0. Whereas the metal ions Na+, Ca2+, and K+ enhanced the activity of the enzyme, others such as Hg2+, Cu2+, Fe2+, Co2+, and Zn2+ had rendered negative effects. The activity of the enzyme was inhibited by EDTA and enhanced by Cu2+ ions, thus indicating the nature of the enzyme as a metalloprotease. The enzyme showed extreme stability and activity even in the presence of detergents, surfactants, and organic solvents. Moreover, the present findings opened new vistas in the utilization of wheat bran, a cheap, abundantly available, and effective waste as a substrate for SSF.
Text Mining in Biomedical Domain with Emphasis on Document Clustering
Vinaitheerthan Renganathan 대한의료정보학회 2017 Healthcare Informatics Research Vol.23 No.3
Objectives: With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. Methods: This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Results: Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Conclusions: Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.
Srirambalaji, Renganathan,Hong, Soonsang,Natarajan, Ramalingam,Yoon, Minyoung,Hota, Raghunandan,Kim, Yonghwi,Ho Ko, Young,Kim, Kimoon The Royal Society of Chemistry 2012 Chemical communications Vol.48 No.95
<P>A metal–organic framework (MOF), NH<SUB>2</SUB>-MIL-101(Al), which acts as a bifunctional, site-isolated Lewis acid–Brønsted base heterogeneous catalyst, catalyzes a tandem Meinwald rearrangement–Knoevenagel condensation reaction with remarkable substrate selectivity.</P> <P>Graphic Abstract</P><P>A bifunctional MOF, NH<SUB>2</SUB>-MIL-101(Al), catalyzes tandem Meinwald rearrangement–Knoevenagel condensation with remarkable substrate selectivity. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c2cc36678a'> </P>
Nanocrystalline cerium oxide coated fiber optic gas sensor
B. Renganathan,D. Sastikumar,A. Chandra Bose,R. Srinivasan,A.R. Ganesan 한국물리학회 2014 Current Applied Physics Vol.14 No.3
A clad-modified fiber optic sensor with nanocrystalline CeO2 is proposed for gas detection. As-prepared and annealed CeO2 (500 C) samples have been used as gas sensing media. The spectral characteristics of the fiber optic gas sensor are studied for various concentrations of ammonia, ethanol and methanol gases (0e500 ppm). The sensor exhibits linear variation in the spectral peak intensity with the gas concentration. The characteristics of the sensor are also studied for gas selectivity. The time response characteristics of the sensor are reported.
Ramachandran Kasirajan,Renganathan Sahadevan,Sivakumar Pandian,Suganya Tamilarasan 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.3
The lipid content was extracted from the saga seed by superheated condition and soxhlet apparatus. Themixture of hexane, chloroform and methanol was utilized as a mixed solvent for these extraction operations. Differentparameters such as different solvent, temperature, mean particle size and solvent flow have been examined. The optimizedlipid extraction was achieved as 26.2 wt% by using superheated condition from the saga seed powder at 90 oCfor 120min. Then the fatty acids profile of the optimized Adenanthera pavonina oil were analyzed by gas chromatography. Unsaturated fatty acid was high as 83.7% compared with saturated fatty acid barely 15.4% by relative.
( Gurunathan Baskar ),( Renganathan Sahadevan ) 한국미생물 · 생명공학회 2012 Journal of microbiology and biotechnology Vol.22 No.7
Optimization of culture conditions for L-asparaginase production by submerged fermentation of Aspergillus terreus MTCC 1782 was studied using a 3-level central composite design of response surface methodology and artificial neural network linked genetic algorithm. The artificial neural network linked genetic algorithm was found to be more efficient than response surface methodology. The experimental L-asparaginase activity of 43.29 IU/ml was obtained at the optimum culture conditions of temperature 35oC, initial pH 6.3, inoculum size 1% (v/v), agitation rate 140 rpm, and incubation time 58.5 h of the artificial neural network linked genetic algorithm, which was close to the predicted activity of 44.38 IU/ml. Characteristics of L-asparaginase production by A. terreus MTCC 1782 were studied in a 3 L bench-scale bioreactor.
Generalized Analysis of Gasifier Performance using Equilibrium Modeling
Ravikiran, Anapagaddi,Renganathan, Thiruvengadam,Pushpavanam, Subramaniam,Voolapalli, Ravi Kumar,Cho, Young Sang American Chemical Society 2012 INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH - Vol.51 No.4
<P>Thermodynamic modeling of gasification process provides a quick estimate of performance of the gasifier. Most of the earlier work on thermodynamic modeling is restricted to a particular feedstock–gasification agent combination and hence the results cannot be generalized. In the present work, the equilibrium modeling based on Gibb’s free energy minimization approach is used to analyze the performance of gasification of any fuel using oxygen or steam. The performance is analyzed at the carbon boundary point at which the cold gas efficiency is maximum. The gasification temperature, amount of gasification agent required, composition of syngas, and cold gas efficiency are predicted using Aspen Plus. The results are presented as contour plots on Van Krevelen coordinates (<I>H/C</I> vs <I>O/C</I>) and interpreted based on simplified gasification reactions. The performance for different feedstocks represented in Van Krevelen diagram is also analyzed. Finally, advantage of cogasification of feedstocks is highlighted.</P>
Baskar Gurunathan,Renganathan Sahadevan 한국생물공학회 2011 Biotechnology and Bioprocess Engineering Vol.16 No.1
The sequential optimization strategy for design of an experimental and artificial neural network (ANN)linked genetic algorithm (GA) were applied to evaluate and optimize media component for L-asparaginase production by Aspergillus terreus MTCC 1782 in submerged fermentation. The significant media components identified by Plackett-Burman design (PBD) were fitted into a second order polynomial model (R^2 = 0.910) and optimized for maximum L-asparaginase production using a five-level central composite design (CCD). A nonlinear model describing the effect of variables on L-asparaginase production was developed (R^2 = 0.995) and optimized by a back propagation NN linked GA. Ground nut oil cake (GNOC)flour 3.99% (w/v), sodium nitrate (NaNO_3) 1.04%, Lasparagine 1.84%, and sucrose 0.64% were found to be the optimum concentration with a maximum predicted Lasparaginase activity of 36.64 IU/mL using a back propagation NN linked GA. The experimental activity of 36.97IU/mL obtained using the optimum concentration of media components is close to the predicted L-asparaginase activity of the ANN linked GA.
M. Parthibavarman,B. Renganathan,D. Sastikumar 한국물리학회 2013 Current Applied Physics Vol.13 No.7
We have successfully synthesized Co doped SnO2 nanoparticles by a simple microwave irradiation technique. Powder X-ray diffraction results reveal that the SnO2 doped with cobalt concentration from 0 to 5 wt % crystallizes in tetragonal rutile-type structure. The products were annealed at 600 ℃ for 5 h in ambient atmosphere in order to improve crystallinity and structural perfection. Transmission electron microscopy (TEM) studies illustrate that both the undoped and Co doped SnO2 crystallites form in spherical shapes with an average diameter of 30e15 nm, which is in good agreement with the average crystallite sizes calculated by Scherrer’s formula. A considerable red shift in the absorbing band edge was observed with increasing of Co content (0-5 wt %) by using UVeVis diffuse reflectance spectroscopy (DRS). Oxygen-vacancies, tin interstitial and structural defects were analyzed using photoluminescence (PL) spectroscopy. Electron paramagnetic resonance (EPR) spectroscopic studies clearly showed that the Co2+ was incorporated into the SnO2 host lattice. Ethanol gas sensitivity of pure and Co-doped (5 wt %)SnO2 nanoparticles were experimented at ambient temperature using optical fiber based on cladmodified method. By modifying the clad exposure to ethanol vapor, the sensitivities were estimated to be 18 and 30 counts/100 ppm for undoped and Co-doped SnO2 nanoparticles, respectively. These results show that the Co doping into SnO2 enhances its ethanol gas sensitivity significantly.