02018nas a2200217 4500008004100000022001400041245009200055210006900147260006800216300001400284490000800298520122500306653001301531653001601544653003301560100002401593700002301617700001801640700002201658856012001680 2008 eng d a0021-899500aModeling of a fluidized bed propylene polymerization reactor operated in condensed mode0 aModeling of a fluidized bed propylene polymerization reactor ope a111 RIVER ST, HOBOKEN, NJ 07030 USAbJOHN WILEY & SONS INCcMAY a2067-20760 v1083 a

The gas-phase polymerization of propylene is one of the most widely accepted and commercially used processes for the manufacture of polypropylene (PP). Because of the highly exothermic nature of polymerization reactions, temperature runaway and subsequent polymer melting and agglomeration may occur, and the reactor has to be operated in a small operating window for safety. The addition of liquid monomer for heat removal (condensed mode) broadens the operating window and can substantially increase (by 50-100%) the capacity of given reactor hardware. This article describes the extension of a comprehensive mathematical model for the simulation of fluidized bed PP reactors to include the condensed mode of operations. The model is used to determine the influence of the operating parameters on the polymer properties and particle size distribution. The model is also used to determine the effects of two active sites and the reaction kinetics on macroscopic variables. The developed framework is useful for simulating multimonomer, multisite Ziegler-Natta-type olefin fluidized bed polymerization reactors operated under condensed mode. (C) 2008 Wiley Periodicals, Inc. J Appl Polym Sci 108: 2067-2076, 2008.

10aModeling10aPolyolefins10aZiegler-Natta polymerization1 aUtikar, Ranjeet, P.1 aHarshe, Yogesh, M.1 aMehra, Anurag1 aRanade, Vivek, V. uhttp://library.ncl.res.in/content/modeling-fluidized-bed-propylene-polymerization-reactor-operated-condensed-mode-002104nas a2200265 4500008004100000022001400041245009600055210006900151260006900220300001200289490000700301520118700308653002801495653002001523653001701543653001301560653001701573653001301590100002001603700002201623700002601645700002101671700001701692856012901709 2008 eng d a1369-703X00aOptimal xylanase production using Penicilium janthinellum NCIM 1169: a model based approach0 aOptimal xylanase production using Penicilium janthinellum NCIM 1 aPO BOX 564, 1001 LAUSANNE, SWITZERLANDbELSEVIER SCIENCE SAcJUN a348-3560 v403 a

Xylanases are an industrially important class of hydrolytic enzymes that degrade xylans. Production of xylanase from a fungal culture by submerged fermentation and optimization of the operating conditions for maximum activity are the two aims of the present study. Penicillium janthinellum NCIM 1169 with Mandels-Weber medium, sugarcane bagassse (40\#) as a carbon source and beef extract as a nitrogen source were used in the experiments. We did 41 experiments to see the effect of variations in carbon, nitrogen source, pH, and inoculum on xylanase activity. This data was then used to build an input/output model using multiple linear regression, back propagation neural network and lazy learning algorithm. It was found that lazy learning model correlated well in mapping input/output data. This model was then utilized as an objective function in genetic algorithm to find the optimal combination of the operating conditions to get the maximum xylanase activity. It was observed that with carbon source, 1.63%, nitrogen source, 0.16%, pH, 4.1, and inoculum, 5.5%, maximum xylanase activity of 28.98 +/- 1.73 U/ml was achieved. (C) 2008 Elsevier B.V. All rights reserved.

10aArtificial intelligence10aEnzyme activity10aFermentation10aModeling10aOptimization10aXylanase1 aMeshram, Mukesh1 aKulkarni, Abhijit1 aJayaraman, Valadi, K.1 aKulkarni, B., D.1 aLele, S., S. uhttp://library.ncl.res.in/content/optimal-xylanase-production-using-penicilium-janthinellum-ncim-1169-model-based-approach-001888nas a2200229 4500008004100000022001400041245010200055210006900157260010000226300001400326490000700340520096800347653004401315653002601359653001301385653001301398653005301411100002501464700002601489700002201515856012101537 2010 eng d a0266-353800aPolyethersulfone-expanded graphite nanocomposites: charge transport and impedance characteristics0 aPolyethersulfoneexpanded graphite nanocomposites charge transpor aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLANDbELSEVIER SCI LTDcNOV0 a2111-21160 v703 a

Polyethersulfone (PES)-expanded graphite nanocomposites have been prepared by solution blending route after sonicating expanded graphite in dichloromethane. It has been observed that ultrasonication results in nanosheets formation leading to a low percolation threshold of 3 wt.%. At 5 wt.% filler loading the conductivity is of the order of 10(-2) S/cm. Hopping type of charge transport occurs at 3.2 wt.% expanded graphite in PES below which capacitive effects couple. The effective dielectric constant at low frequency increases with filler concentration. Impedance measurement has been carried out to evaluate interfacial capacitance which, for 3.2 wt.% expanded graphite addition in PES, increases to 110 pF from 32 pF for 1 wt.% expanded graphite in the polymer. DSC analysis shows an increment of 12 C in the T(g) of PES with 3 wt.% expanded graphite suggesting interaction between the polymer and filler. (C) 2010 Elsevier Ltd. All rights reserved.

10aDifferential scanning calorimetry (DSC)10aElectrical properties10aModeling10aPolymers10aScanning/transmission electron microscopy (STEM)1 aRamanujam, B., T. S.1 aMahale, Rajashree, Y.1 aRadhakrishnan, S. uhttp://library.ncl.res.in/content/polyethersulfone-expanded-graphite-nanocomposites-charge-transport-and-impedance-002026nas a2200205 4500008004100000022001400041245011500055210006900170260006700239300001000306490000700316520126400323653001301587653001801600653001301618653001401631653002401645100002901669856012201698 2014 eng d a0730-667900aPhotopolymerization kinetics of block polyether based terminal urethane methacrylate with/without cross-linker0 aPhotopolymerization kinetics of block polyether based terminal u a111 RIVER ST, HOBOKEN 07030-5774, NJ USAbWILEY-BLACKWELLcFEB a214180 v333 a

The present work deals with the photopolymerization of difunctional macromonomer with a polyether chain and urethane methacrylate terminations. Macromonomeric formulations were prepared by mixing macromonomer with two different concentrations of photoinitiator. Formulations were also prepared by the addition of 10 wt% of soft-segmented difunctional cross-linker to the abovementioned macromonomic formulations. All formulations were then subjected to photopolymerization studies and the effects of light intensity on the photopolymerization kinetics were studied at two different isothermal conditions using photo differential scanning calorimetry (Photo DSC) with polychromatic radiation. The isothermal heat flow against time was recorded for all formulations and the kinetic parameters were noted. It was observed that the rate of maximum polymerization as well as peak maximum time showed a general trend. However, the ultimate conversion as well as the conversion at maximum rate did not show any trend due to diffusional restrictions imparted by the increase in viscosity with conversion. The photopolymerization of the formulations and curing kinetics including evaluation of autocatalytic model are discussed. (C) 2014 Wiley Periodicals, Inc.

10akinetics10aMacromonomers10aModeling10aPhoto DSC10aPhotopolymerization1 aReghunathan, Harikrishna uhttp://library.ncl.res.in/content/photopolymerization-kinetics-block-polyether-based-terminal-urethane-methacrylate-002601nas a2200229 4500008004100000022001400041245007800055210006900133260007300202300001100275490000700286520181600293653002802109653002102137653002602158653001102184653001302195653001202208100001802220700002302238856011002261 2014 eng d a1369-703X00aSoft-sensor development for biochemical systems using genetic programming0 aSoftsensor development for biochemical systems using genetic pro aPO BOX 211, 1000 AE AMSTERDAM, NETHERLANDSbELSEVIER SCIENCE BVcAPR a89-1000 v853 a

Soft-sensors are software based process monitoring systems/models. In real-time they estimate those process variables, which are difficult to measure online or whose measurement by analytical procedures is tedious and time-consuming. In this study, the genetic programming (GP), an artificial intelligence based data-driven modeling formalism, has been introduced for the development of soft-sensors for biochemical processes. The novelty of the GP is that given example input-output data, it searches and optimizes both the form (structure) and parameters of an appropriate linear/nonlinear data-fitting model. In this study, GP-based soft-sensors have been developed for two bioprocesses, namely extracellular production of lipase enzyme and bacterial production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) copolymer. While in case study-I, the soft-sensor predicts the time-dependent lipase activity (U/ml), in case study-II it predicts the amount of accumulated polyhydroxyalkanoates (% dcw). The prediction and generalization performance of the GP-based soft-sensors was compared with the corresponding multi-layer perceptron (MLP) neural network and support vector regression (SVR) based soft-sensors. This comparison indicates that in the first case study the GP-based soft-sensor with the training and test set correlation coefficient (root-mean-squared-error) magnitudes of >0.96 (approximate to 0.962 U/ml) has clearly outperformed the two other soft-sensors. In case study-II involving bacterial copolymer production, the GP and SVR based soft-sensors have performed equally well (correlation coefficient approximate to 0.98) while the MLP based soft-sensor's performance was relatively inferior (correlation coefficient approximate to 0.94). (C) 2014 Elsevier B.V. All rights reserved.

10aArtificial intelligence10aBatch processing10aBioprocess monitoring10aLipase10aModeling10asensors1 aSharma, Suraj1 aTambe, Sanjeev, S. uhttp://library.ncl.res.in/content/soft-sensor-development-biochemical-systems-using-genetic-programming-001853nas a2200265 4500008004100000022001400041245010800055210006900163260000900232300000800241490000700249520099900256653001901255653002501274653001501299653001301314653002501327653001601352653001801368653001501386100002301401700001901424700002401443856012001467 2019 eng d a1664-302X00aWeb-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations0 aWebgLV a web based platform for lotkavolterra based modeling and cFEB  a2880 v103 a

The affordability of high throughput DNA sequencing has allowed us to explore the dynamics of microbial populations in various ecosystems. Mathematical modeling and simulation of such microbiome time series data can help in getting better understanding of bacterial communities. In this paper; we present Web-gLV- a GUI based interactive platform for generalized Lotka-Volterra (gLV) based modeling and simulation of microbial populations. The tool can be used to generate the mathematical models with automatic estimation of parameters and use them to predict future trajectories using numerical simulations. We also demonstrate the utility of our tool on few publicly available datasets. The case studies demonstrate the ease with which the current tool can be used by biologists to model bacterial populations and simulate their dynamics to get biological insights. We expect Web-gLV to be a valuable contribution in the field of ecological modeling and metagenomic systems biology.

10alotka-volterra10amicrobial population10aMicrobiome10aModeling10anumerical-simulation10atime-series10avisualization10aweb-server1 aKuntal, Bhusan, K.1 aGadgil, Chetan1 aMande, Sharmila, S. uhttp://library.ncl.res.in/content/web-glv-web-based-platform-lotka-volterra-based-modeling-and-simulation-microbial00867nas a2200253 4500008004100000022001400041245012800055210006900183260000900252300001100261490000700272653001900279653002500298653001500323653001300338653002500351653001600376653001800392653001500410100002300425700001900448700002400467856012200491 2021 eng d a1664-302X00aWeb-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations (vol 10, 288, 2019)0 aWebgLV a web based platform for lotkavolterra based modeling and cJAN  a6053080 v1110alotka-volterra10amicrobial population10aMicrobiome10aModeling10anumerical-simulation10atime-series10avisualization10aweb-server1 aKuntal, Bhusan, K.1 aGadgil, Chetan1 aMande, Sharmila, S. uhttp://library.ncl.res.in/content/web-glv-web-based-platform-lotka-volterra-based-modeling-and-simulation-microbial-0