An artificial neural network(ANN) constitutive model and JohnsoneC ook(Je C) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar(SHPB) experiments a...An artificial neural network(ANN) constitutive model and JohnsoneC ook(Je C) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar(SHPB) experiments at various temperatures. A neural network configuration consists of both training and validation, which is effectively employed to predict flow stress. Temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on Johnsone Cook(Je C) model and neural network model was performed. It was observed that the developed neural network model could predict flow stress under various strain rates and temperatures. The experimental stressestrain data obtained from high strain rate compression tests using SHPB over a range of temperatures(25 e300 C), strains(0.05e0.3) and strain rates(1500e4500 s 1) were employed to formulate JeC model to predict the flow stress behaviour of 7017 aluminium alloy under high strain rate loading. The JeC model and the back-propagation ANN model were developed to predict the flow stress of 7017 aluminium alloy under high strain rates, and their predictability was evaluated in terms of correlation coefficient(R) and average absolute relative error(AARE). R and AARE for the J-C model are found to be 0.8461 and 10.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. The predictions of ANN model are observed to be in consistent with the experimental data for all strain rates and temperatures.展开更多
Aim:To analyze the role of cytosolic glutathione S-transferases (cGSTs) and membrane-associated cytosolic GSTs (macGSTs) in prostaglandin biosynthesis and to evaluate the possible interaction between glutathione S-tra...Aim:To analyze the role of cytosolic glutathione S-transferases (cGSTs) and membrane-associated cytosolic GSTs (macGSTs) in prostaglandin biosynthesis and to evaluate the possible interaction between glutathione S-transferases (GSTs) and cyclooxygenase (COX) in vitro.Methods:SDS-PAGE analysis was undertaken for characterization of GSTs,thin layer chromatography (TLC) to monitor the effect of GSTs on prostaglandin biosynthesis from arachi- donic acid (AA) and spectrophotometric assays were done for measuring activity levels of COX and GSTs.Results: SDS-PAGE analysis indicates that macGSTs have molecular weights in the range of 25-28 kDa.In a coupled assay involving GSTs,arachidonic acid and cyclooxygenase-1,rat testicular macGSTs produced prostaglandin E2 and F2~, while the cGSTs caused the generation of prostaglandin D2,E2 and F_(2α).In vitro interaction studies on GSTs and COX at the protein level have shown dose-dependent inhibition of COX activity by macGSTs and vice versa.This effect, however,is not seen with cGSTs.The inhibitory effect of COX on macGST activity was relieved with increasing concentrations of reduced glutathione (GSH) but not with 1-chloro 2,4-dinitrobenzene (CDNB).The inhibition of COX by macGSTs,on the other hand,was potentiated by glutathione.Conclusion:We isolated and purified macGSTs and cGSTs from rat testis and analyzed their involvement in prostaglandin biosynthesis.These studies reveal a revers- ible functional interaction between macGSTs and COX in vitro,with possible interactions between them at the GSH binding site of macGSTs.展开更多
We present here experimental results on the optimization of the mega-electronvolt ion source from the target front surface by using relativistic(10^(18)W/cm^(2))interactions with ultra-short laser pulses(50 fs).The so...We present here experimental results on the optimization of the mega-electronvolt ion source from the target front surface by using relativistic(10^(18)W/cm^(2))interactions with ultra-short laser pulses(50 fs).The source perturbation in the accelerated proton/ion beam was primarily controlled by the addition of a pre-pulse to main pulse contrast ratio.The 2D particle-in-cell simulations agreed well with the observed experimental results for the ion source perturbation and mitigation.This work provides insights into ion source perturbations(temporal and spatial)and the need to control them in intense laser–plasma interactions.Our results may assist in the efficient guiding of proton/ion beams to the core of fusion fuel or of ions in cancer therapy.展开更多
基金Defence Research and Development Organization, India for financial help in carrying out the experiments
文摘An artificial neural network(ANN) constitutive model and JohnsoneC ook(Je C) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar(SHPB) experiments at various temperatures. A neural network configuration consists of both training and validation, which is effectively employed to predict flow stress. Temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on Johnsone Cook(Je C) model and neural network model was performed. It was observed that the developed neural network model could predict flow stress under various strain rates and temperatures. The experimental stressestrain data obtained from high strain rate compression tests using SHPB over a range of temperatures(25 e300 C), strains(0.05e0.3) and strain rates(1500e4500 s 1) were employed to formulate JeC model to predict the flow stress behaviour of 7017 aluminium alloy under high strain rate loading. The JeC model and the back-propagation ANN model were developed to predict the flow stress of 7017 aluminium alloy under high strain rates, and their predictability was evaluated in terms of correlation coefficient(R) and average absolute relative error(AARE). R and AARE for the J-C model are found to be 0.8461 and 10.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. The predictions of ANN model are observed to be in consistent with the experimental data for all strain rates and temperatures.
文摘Aim:To analyze the role of cytosolic glutathione S-transferases (cGSTs) and membrane-associated cytosolic GSTs (macGSTs) in prostaglandin biosynthesis and to evaluate the possible interaction between glutathione S-transferases (GSTs) and cyclooxygenase (COX) in vitro.Methods:SDS-PAGE analysis was undertaken for characterization of GSTs,thin layer chromatography (TLC) to monitor the effect of GSTs on prostaglandin biosynthesis from arachi- donic acid (AA) and spectrophotometric assays were done for measuring activity levels of COX and GSTs.Results: SDS-PAGE analysis indicates that macGSTs have molecular weights in the range of 25-28 kDa.In a coupled assay involving GSTs,arachidonic acid and cyclooxygenase-1,rat testicular macGSTs produced prostaglandin E2 and F2~, while the cGSTs caused the generation of prostaglandin D2,E2 and F_(2α).In vitro interaction studies on GSTs and COX at the protein level have shown dose-dependent inhibition of COX activity by macGSTs and vice versa.This effect, however,is not seen with cGSTs.The inhibitory effect of COX on macGST activity was relieved with increasing concentrations of reduced glutathione (GSH) but not with 1-chloro 2,4-dinitrobenzene (CDNB).The inhibition of COX by macGSTs,on the other hand,was potentiated by glutathione.Conclusion:We isolated and purified macGSTs and cGSTs from rat testis and analyzed their involvement in prostaglandin biosynthesis.These studies reveal a revers- ible functional interaction between macGSTs and COX in vitro,with possible interactions between them at the GSH binding site of macGSTs.
基金support from the SERB Imprint Project No.IMP/2019/000275
文摘We present here experimental results on the optimization of the mega-electronvolt ion source from the target front surface by using relativistic(10^(18)W/cm^(2))interactions with ultra-short laser pulses(50 fs).The source perturbation in the accelerated proton/ion beam was primarily controlled by the addition of a pre-pulse to main pulse contrast ratio.The 2D particle-in-cell simulations agreed well with the observed experimental results for the ion source perturbation and mitigation.This work provides insights into ion source perturbations(temporal and spatial)and the need to control them in intense laser–plasma interactions.Our results may assist in the efficient guiding of proton/ion beams to the core of fusion fuel or of ions in cancer therapy.
