A method to extract crude heparin sodium from pig intestinal mucosa by dialysis and spray drying was established. The pig intestinal mucosa was treated in the following steps: enzymolysis, resin exchange adsorption-wa...A method to extract crude heparin sodium from pig intestinal mucosa by dialysis and spray drying was established. The pig intestinal mucosa was treated in the following steps: enzymolysis, resin exchange adsorption-washing, elution, pressure filtration, dialysis, spray drying. Activity of the product was measured using a heparin anti-IIa factor assay kit. The yield of crude heparin obtained by this method was 2.79% higher than that of oven drying method;the production of 1 kg crude heparin sodium saved 43.4 pigs small intestine. The activity was 98.48 ± 2.49 IU/mg (n = 5), 15.18 IU/mg higher than that obtained by oven drying method. The product is pale white powder, attractive color and easy to dissolve.展开更多
Background:The simplest and most convenient food technology is the using of dry composite mixtures.They have a lot of advantages.Dry composite mixtures,which would completely be the basis for the production of persona...Background:The simplest and most convenient food technology is the using of dry composite mixtures.They have a lot of advantages.Dry composite mixtures,which would completely be the basis for the production of personalized food concentrates,are not represented.The development of such dry composite mixtures is actual and of scientific and practical interest.The purpose of this research is the selection and justification of local import-substituting raw materials components for dry composite mixtures used as the basis for the production of food concentrates.As the objects of research,the raw materials components of the starch,fruit and vegetable,industry were selected.The work uses currently accepted standard research methods for organoleptic and physic-chemical parameters of raw materials components.The research was carried out within of the project“Theoretical Substantiation of Production Technology and the Development of Import-Substituting Food Products of Functional Purpose Based on Dry Composite Mixtures”,funded by the Belarusian Republican Foundation for Basic Research.Based on the researches,it was found out that in the composition of dry composite mixtures for the production of food concentrates it is expedient to use the following raw materials:potato starch,extruded corn starch,dried carrots,dried beets,dried topinambur and dried apples in chopped form.展开更多
This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimiz...This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.展开更多
文摘A method to extract crude heparin sodium from pig intestinal mucosa by dialysis and spray drying was established. The pig intestinal mucosa was treated in the following steps: enzymolysis, resin exchange adsorption-washing, elution, pressure filtration, dialysis, spray drying. Activity of the product was measured using a heparin anti-IIa factor assay kit. The yield of crude heparin obtained by this method was 2.79% higher than that of oven drying method;the production of 1 kg crude heparin sodium saved 43.4 pigs small intestine. The activity was 98.48 ± 2.49 IU/mg (n = 5), 15.18 IU/mg higher than that obtained by oven drying method. The product is pale white powder, attractive color and easy to dissolve.
文摘Background:The simplest and most convenient food technology is the using of dry composite mixtures.They have a lot of advantages.Dry composite mixtures,which would completely be the basis for the production of personalized food concentrates,are not represented.The development of such dry composite mixtures is actual and of scientific and practical interest.The purpose of this research is the selection and justification of local import-substituting raw materials components for dry composite mixtures used as the basis for the production of food concentrates.As the objects of research,the raw materials components of the starch,fruit and vegetable,industry were selected.The work uses currently accepted standard research methods for organoleptic and physic-chemical parameters of raw materials components.The research was carried out within of the project“Theoretical Substantiation of Production Technology and the Development of Import-Substituting Food Products of Functional Purpose Based on Dry Composite Mixtures”,funded by the Belarusian Republican Foundation for Basic Research.Based on the researches,it was found out that in the composition of dry composite mixtures for the production of food concentrates it is expedient to use the following raw materials:potato starch,extruded corn starch,dried carrots,dried beets,dried topinambur and dried apples in chopped form.
基金This project received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 813393the funding from the National Natural Science Foundation of China (No. 52177149)
文摘This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.
