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Zinc Metal Solubilization by Gluconacetobacter diazotrophicus and Induction of Pleomorphic Cells
( Saravanan ),( Venkatakrishnan Sivaraj ),( Jabez Osborne ),( Munusamy Madhaiyan ),( Lazar Mathew ),( Jong Bae Chung ),( Ki Sup Ahn ),( Tong Min Sa ) 한국미생물생명공학회 2007 Journal of microbiology and biotechnology Vol.17 No.9
Saravanan Prabhu Nadarajan,카나가벨디판쿠마,서주현,윤형돈 한국생물공학회 2017 Biotechnology and Bioprocess Engineering Vol.22 No.5
In the past decade, numerous studies have been reported that the residue specific incorporation of fluorine containing analogs into protein can enhance the stability of protein. On the other hand, the incorporation of fluoroproline can enhance both stability and refolding rate of recombinant proteins. The objective of this study was to determine the reason behind the enhanced stability and refolding rate of protein by comparing GFP variants containing fluoroproline or hydroxyproline. The fluorine atom of 4-fluoroproline played a significant role in enhancing stability, and Cγ-endo puckering property of (4S)-4-fluoroproline and (4S)-4- hydroxyproline plays a key role in enhancing protein refolding rate.
Oral glucose tolerance test for preoperative assessment of liver function in liver resection
Saravanan Manickam Neethirajan,Raghavendra Rao Rachapoodivenk 한국간담췌외과학회 2017 Annals of hepato-biliary-pancreatic surgery Vol.21 No.1
Backgrounds/Aims: We intended to determine the role of the Oral glucose tolerance test (OGTT), in addition to volumetry, in preoperative assessment of patients undergoing liver resection. Methods: This was a prospective study conducted at a tertiary care hospital, between February 2009 and February 2011. OGTT curve (parabolic/linear), linearity index (LI) and Parenchymal Hepatic Resection Rate (PHRR) were correlated with postoperative outcomes in terms of postoperative liver failure (PLF), by 50-50 criteria, morbidity, mortality and hospital stay. Results: Of the 33 patients included in the study, 23 (69.7%) patients underwent major liver resections. Hepatocellular carcinoma (30.3%) was the leading indication. The overall postoperative morbidity rate was 72.7%, but major complications occurred in 3 (9.1%) patients only. There was no 90-day mortality. The 50-50 criteria were met by 3 patients undergoing major resection. Significant correlation was noted between the linear OGTT curve and the overall hospital stay (12.1 days vs. 9.6 days in parabolic; p=0.04). Patients with linear OGTT met the 50-50 criteria more often (18%) than those having a parabolic curve (4.5%; p=0.25). Although the OGTT was more often linear with occurrence of morbidity (41.7% vs 11.1%), major morbidity (66.7% vs 30%) and PLF by 50-50 criteria (66.7% vs 30%), it was not statistically significant. The linearity index was marginally lower (0.9 vs 1.2) in the presence of major morbidity and PLF by 50-50 criteria. Conclusions: Linear OGTT affects the PLF and major morbidity, therein impacting the hospital stay. OGTT LI and PHRR can help predict postoperative outcome for a given extent of liver resection.
Analysis of Neural Network Approaches for Nonlinear Modeling of Switched Reluctance Motor Drive
Saravanan, P,Balaji, M,Balaji, Nagaraj K,Arumugam, R The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1
This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.
Generation Scheduling with Large-Scale Wind Farms using Grey Wolf Optimization
Saravanan, R.,Subramanian, S.,Dharmalingam, V.,Ganesan, S. The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1
Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.
Analysis of Neural Network Approaches for Nonlinear Modeling of Switched Reluctance Motor Drive
Saravanan P,Balaji M,Balaji Nagaraj K,Arumugam R 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.4
This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.
Experimental investigations on composite slabs to evaluate longitudinal shear strength
Saravanan, M.,Marimuthu, V,Prabha, P.,Arul Jayachandran, S.,Datta, D. 국제구조공학회 2012 Steel and Composite Structures, An International J Vol.13 No.5
Cold-formed steel profile sheets acting as decks have been popularly used in composite slab systems in steel structural works, since it acts as a working platform as well as formwork for concreting during construction stage and also as tension reinforcement for the concrete slab during service. In developing countries like India, this system of flooring is being increasingly used due to the innate advantage of these systems. Three modes of failure have been identified in composite slab such as flexural, vertical shear and longitudinal shear failure. Longitudinal shear failure is the one which is difficult to predict theoretically and therefore experimental methods suggested by Eurocode 4 (EC 4) of four point bending test is in practice throughout world. This paper presents such an experimental investigation on embossed profile sheet acting as a composite deck where in the longitudinal shear bond characteristics values are evaluated. Two stages, brittle and ductile phases were observed during the tests. The cyclic load appears to less effect on the ultimate shear strength of the composite slab.
Saravanan, Manoharan,Nam, Sang-Eun,Eom, Hye-Jin,Lee, Do-Hee,Rhee, Jae-Sung Elsevier 2019 COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY C-TOXICOLO Vol.216 No.-
<P><B>Abstract</B></P> <P>Low concentrations of nonylphenol (NP) in aquatic environment can induce drastic effects on the endocrine system in animals. In this study, we examined the modulatory effects of NP on reproductive and physiological parameters in juveniles of the red seabream and black rockfish following waterborne NP exposure (0, 1, 10, and 50 μg L<SUP>−1</SUP>) for 60 days. In red seabream exposed to 50 μg L<SUP>−1</SUP> NP, plasma levels of 17β-estradiol (E2) and 11-ketotestosterone (11-KT) were significantly lower at 30 and 60 days, while E2 levels were slightly higher in 10 μg L<SUP>−1</SUP>-exposed individuals at day 30. Similarly, significantly lower levels of E2 and 11-KT were observed in 10 and 50 μg L<SUP>−1</SUP>-exposed black rockfish at 60 days, whereas the E2 level was higher in 1 μg L<SUP>−1</SUP>-exposed individuals at day 30. After exposure to NP, plasma and mRNA levels of vitellogenin (VTG) were significantly higher in both species at 30 and 60 days, similar to the inducible effects from synthetic estrogen. Plasma cortisol levels were significantly elevated by relatively higher concentrations of NP (10 and 50 μg L<SUP>−1</SUP>) at 30 and 60 days. Finally, 60 days of exposure of 50 μg L<SUP>−1</SUP> NP significantly decreased the gonadosomatic index (GSI) and increased the hepatosomatic index (HSI) in both species. The results obtained from this study provide an evidence of the endocrine disrupting potential of waterborne NP on early stages of economically important marine fish. The NP-triggered endocrine modulation can induce effects on the development of reproductive and metabolic organs in fish species.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Direct evidence on accumulation of waterborne NP in marine fish blood. </LI> <LI> Strong endocrine disruption potential of NP on juvenile stage of marine fish. </LI> <LI> Analysis of NP-triggered stress induction and modulation of somatic parameters. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>