Kinetics Modelling of Pseudomonas stutzeri strain DN2 Growth Behaviour in Tributyltin Chloride

A predictive model was performed to describe Pseudomonas stutzeri strain DN2 growth behaviour in tributyltin chloride, using primary Modelling and a polynomial model as a secondary predictive model. In this investigation, data predicted using the modified Logistic (ML) was the most accurate. The Bias Factor (Bf) and Accuracy Factor (Af) values for the (ML) model were 1.39 and 1.51, indicating that the predictions were within a reliable range. The low RMSE value of 0.14, R2 and adj R2 (0.99) value closer to 1, showing that modified logistics is better than the other models at describing the growth behaviour of Pseudomonas stutzeri strain DN2 in toxic tributyltin chloride. Both the Aiba and Haldane models on the other hand, among the secondary model best fit the behaviours having low RMSE and MSE values and adjR2 value closer to 1. In this study, the primary and secondary kinetics of Pseudomonas stutzeri strain DN2 growth behaviour in tributyltin chloride was explored and it was shown in this study that the modified logistic and the Haldane models better suit the growth behavior of Pseudomonas stutzeri strain DN2 in tributyltin chloride. The parameters obtained from the modelling exercise will be very valuable in transferring the laboratory results to the field.

Exact solutions for the formation of stagnant caps of insoluble surfactant on a planar free surface

A class of exact solutions is presented describing the time evolution of insoluble surfactant to a stagnant cap equilibrium on the surface of deep water in the Stokes flow regime at zero capillary number and infinite surface Péclet number. This is done by demonstrating, in a two-dimensional model setting, the relevance of the forced complex Burgers equation to this problem when a linear equation of state relates the surface tension to the surfactant concentration. A complex-variable version of the method of characteristics can then be deployed to find an implicit representation of the general solution. A special class of initial conditions is considered for which the associated solutions can be given explicitly. The new exact solutions, which include both spreading and compactifying scenarios, provide analytical insight into the unsteady formation of stagnant caps of insoluble surfactant. It is also shown that first-order reaction kinetics modelling sublimation or evaporation of the insoluble surfactant to the upper gas phase can be incorporated into the framework; this leads to a forced complex Burgers equation with linear damping. Generalized exact solutions to the latter equation at infinite surface Péclet number are also found and used to study how reaction effects destroy the surfactant cap equilibrium.

Synthesis and characterization of bio catalyst prepared from dairy waste for lactic acid esterification

Dairy byproduct is known for its valuable chemical and nutritional content possessing high market potential. Notwithstanding, it is tractable to exploit its utilization. The waste generated is organic and having huge energy potential. The objective of current research is to synthesize novel catalyst from a dairy based solid waste called Ghee Residue by chemical activation process and deploy it for the production of iso-butyl lactate. Surface identity of catalyst was furnished using Brunauer-Emmet Teller (BET) method and Fourier Transform Infrared Spectroscopy (FTIR). Effect of variables like reaction time, temperature of reaction and loading of catalyst on lactic acid conversion were studied. In addition to this, reaction kinetics modelling was performed using 2nd order pseudo-homogeneous approach. It was inferred that, both internal as well as external resistance of mass transfer could not offer any influence on overall rate of reaction in this esterification. Optimum condition for esterification reaction was at 368 K with 3% catalyst loading giving the highest conversion around 74%. The energy of activation for the present system using synthesized catalyst was 41.5 kJ/mol and found to be lower in comparison with the other catalysts. Although, the activity of GRC declined gradually less than 10% from the activity of the several reaction cycle.

End-to-end computational approach to the design of RNA biosensors for miRNA biomarkers of cervical cancer

Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50 percent mortality rate. Poor awareness and access to effective diagnosis have led to this enormous disease burden, calling for point–of–care, minimally invasive diagnosis methods. Here, an end to end quantitative approach for a new kind of diagnosis has been developed, comprising identification of biomarkers, design of the sensor, and simulation of the diagnostic circuit. Using miRNA expression data in the public domain, we identified circulating miRNA biomarkers specific to cervical cancer using multi–tier screening. Synthetic riboregulators called toehold switches specific for the biomarker panel were designed. To predict their dynamic range for use in genetic circuits as biosensors, we built a multivariate linear regression model using a generic grammar of the toehold structure, and thermodynamic features derived from RNA secondary structure and interaction. The model yielded good performance with an adjusted R2 = 0.59. Reaction kinetics modelling was performed to predict the sensitivity of the second–generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10nM and 100nM before saturation. Our study demonstrates an end–to–end workflow for the efficient design of genetic ciruits geared towards the effective detection of unique genomic signatures that would be increasingly important in today's world. The approach has the potential to direct experimental efforts and minimise costs. All resources including the machine learning toolkit, reaction kinetics simulation, designed toehold sequences, genetic circuits, data, and sbml files for replicating and utilizing our study are provided open–source (under GNU GPLv3 licence).