Development of Kinetic and Process Models for the Oxidative Desulfurization of Light Fuel, Using Experiments and the Parameter Estimation Technique

YesThe oxidative desulphurization (ODS) of light gas oil (LGO) is investigated with an in-house designed cobalt 11 oxide loaded on alumina (γ-Al2O3) catalyst in the presence of air as oxidizing agent under moderate operating 12 conditions (temperature from 403 to 473 K, LHSV from 1 to 3 hr-1, initial concentration from 500 to 1000 13 ppm). Incipient Wetness Impregnation method (IWI) of cobalt oxide over gamma alumina (2% Co3O4/γ-14 Al2O3) is used for the preparation of the catalyst. The optimal design of experiments is studied to evaluate the 15 effects of a number of process variables namely temperature, liquid hourly space velocity (LHSV) and 16 concentration of dibenzothiophene and their optimal values were found to be 473 K, 1hr-1 and 1000 ppm 17 respectively. For conversion dibenzothiophene to sulphone and sulphoxide, the results indicates that the 18 Incipient Wetness Impregnation (IWI) is suitable to prepare this type of the catalyst. Based on the 19 experiments, mathematical models that represent a three phase reactor for describing the behavior of the ODS 20 process are developed. 21 In order to develop a useful model for simulation, control, design and scale-up of the oxidation process, 22 accurate evaluation of important process parameters such as reaction rate parameters is absolutely essential. 23 For this purpose, the parameter estimation technique available in gPROMS (general Process Modelling 24 System) software is employed in this work. With the estimated process parameters further simulations of the 25 process is carried out and the concentration profiles of dibenzothiophene within the reactor are generated

GLP-1 receptor signalling promotes β-cell glucose metabolism via mTOR-dependent HIF-1α activation

Glucagon-like peptide-1 (GLP-1) promotes insulin secretion from pancreatic ß-cells in a glucose dependent manner. Several pathways mediate this action by rapid, kinase phosphorylation-dependent, but gene expression-independent mechanisms. Since GLP-1-induced insulin secretion requires glucose metabolism, we aimed to address the hypothesis that GLP-1 receptor (GLP-1R) signalling can modulate glucose uptake and utilization in ß-cells. We have assessed various metabolic parameters after short and long exposure of clonal BRIN-BD11 ß-cells and rodent islets to the GLP-1R agonist Exendin-4 (50 nM). Here we report for the first time that prolonged stimulation of the GLP-1R for 18 hours promotes metabolic reprogramming of ß-cells. This is evidenced by up-regulation of glycolytic enzyme expression, increased rates of glucose uptake and consumption, as well as augmented ATP content, insulin secretion and glycolytic flux after removal of Exendin-4. In our model, depletion of Hypoxia-Inducible Factor 1 alpha (HIF-1a) impaired the effects of Exendin-4 on glucose metabolism, while pharmacological inhibition of Phosphoinositide 3-kinase (PI3K) or mTOR completely abolished such effects. Considering the central role of glucose catabolism for stimulus-secretion coupling in ß-cells, our findings suggest that chronic GLP-1 actions on insulin secretion include elevated ß-cell glucose metabolism. Moreover, our data reveal novel aspects of GLP-1 stimulated insulin secretion involving de novo gene expression

Optimal Design of a Trickle Bed Reactor for Light Fuel Oxidative Desulfurization based on Experiments and Modelling

YesIn this work, the performance of oxidative desulfurization (ODS) of dibenzothiophene (DBT) in light gas oil (LGO) is evaluated with a homemade manganese oxide (MnO2/γ-Al2O3) catalyst. The catalyst is prepared by Incipient Wetness Impregnation (IWI) method with air under moderate operating conditions. The effect of different reaction parameters such as reaction temperature, liquid hour space velocity and initial concentration of DBT are also investigated experimentally. Developing a detailed and a validated trickle bed reactor (TBR) process model that can be employed for design and optimization of the ODS process, it is important to develop kinetic models for the relevant reactions with high accuracy. Best kinetic model for the ODS process taking into account hydrodynamic factors (mainly, catalyst effectiveness factor, catalyst wetting efficiency and internal diffusion) and the physical properties affecting the oxidation process is developed utilizing data from pilot plant experiments. An optimization technique based upon the minimization of the sum of the squared error between the experimental and predicted composition of oxidation process is used to determine the best parameters of the kinetic models. The predicted product conversion showed very good agreement with the experimental data for a wide range of the operating condition with absolute average errors less than 5%

PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA

Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region

Glutamate acts as a key signal linking glucose metabolism to incretin/cAMP action to amplify insulin secretion.

Incretins, hormones released by the gut after meal ingestion, are essential for maintaining systemic glucose homeostasis by stimulating insulin secretion. The effect of incretins on insulin secretion occurs only at elevated glucose concentrations and is mediated by cAMP signaling, but the mechanism linking glucose metabolism and cAMP action in insulin secretion is unknown. We show here, using a metabolomics-based approach, that cytosolic glutamate derived from the malate-aspartate shuttle upon glucose stimulation underlies the stimulatory effect of incretins and that glutamate uptake into insulin granules mediated by cAMP/PKA signaling amplifies insulin release. Glutamate production is diminished in an incretin-unresponsive, insulin-secreting β cell line and pancreatic islets of animal models of human diabetes and obesity. Conversely, a membrane-permeable glutamate precursor restores amplification of insulin secretion in these models. Thus, cytosolic glutamate represents the elusive link between glucose metabolism and cAMP action in incretin-induced insulin secretion