Gas Phase Carbon Dioxide as an Optimum Substrate for Isocitrate Dehydrogenase Reaction

As biocatalytic carbon capture has attracted wide attraction due to its high energy efficiency, the preference of carbon species of the reaction is concerned. The self-evolution between carbon species makes the determination of preference a changeling issue. In this study, by comparing the isocitrate dehydrogenase reaction rate profiles with pre-equilibrated and un-equilibrated HCO3--CO2 solutions, gas phase carbon dioxide was believed as the optimum substrate, as it can provide higher reaction rate. During the carbon capture process, the partial pressure of the carbon dioxide affected both the reaction equilibrium and kinetics, while the interfacial area can only determine the reaction rate

Immobilization of Isocitrate Dehydrogenase on Mesoporous Silica Foam for Carbon Dioxide Capture

Carbon capture can be realized effectively through isocitrate dehydrogenase reaction and the reaction rate was strongly affected by the environmental parameters such as pH and temperature. Enzyme immobilization was conducted to improve the enzyme stability during the capture process. By simply adsorbing enzyme on the surface of mesoporous silica foam, enzyme stability against temperature, pH and shear stress was improved. The immobilization process can be completed in 5 mins, and 0.87 U enzyme activity was kept for each gram of immobilization material. After 10 cycles, more than 50 percent of enzyme activity remained. The reusability and improved stability made immobilized ICDH a better candidate for large-scale application of carbon capture

Catalytic Pyrolysis of Biomass and Polymer Wastes

Oil produced by the pyrolysis of biomass and co-pyrolysis of biomass with waste synthetic polymers has significant potential as a substitute for fossil fuels. However, the relatively poor properties found in pyrolysis oil—such as high oxygen content, low caloric value, and physicochemical instability—hampers its practical utilization as a commercial petroleum fuel replacement or additive. This review focuses on pyrolysis catalyst design, impact of using real waste feedstocks, catalyst deactivation and regeneration, and optimization of product distributions to support the production of high value-added products. Co-pyrolysis of two or more feedstock materials is shown to increase oil yield, caloric value, and aromatic hydrocarbon content. In addition, the co-pyrolysis of biomass and polymer waste can contribute to a reduction in production costs, expand waste disposal options, and reduce environmental impacts. Several promising options for catalytic pyrolysis to become industrially viable are also discussed.Article processing charges for this publication funded in part by the University of Oklahoma Libraries Open Access Fund.Ye

Removal of Asphaltene from Crude Oil by the Electro–Deposition Method

The deposition of asphaltene on interior pipe surfaces is considered a challenging flow assurance issue. By exploiting the net charge of the asphaltene molecule, it can be effectively removed from the flow stream by means of electro–deposition before transportation to prevent later deposition. To evaluate this concept, electro–deposition of asphaltene from a synthetic oil using varying electric field strength and solvent type was studied. Both native charge (positive) and induced charge (negative) of asphaltene were observed in this study; the inducement of charge was realized with higher current density. Asphaltene solubility in the synthetic oil was increased by increasing the polar/non-polar solvent ratio revealing a higher conductivity of the synthetic oil. In addition to electric field strength and synthetic oil composition, the asphaltene concentration and synthetic oil viscosity also affected the electro-deposition.Petroleum Engineering, Department o

Immobilization of Isocitrate Dehydrogenase on Mesoporous Silica Foam for Carbon Dioxide Capture

Carbon capture can be realized effectively through isocitrate dehydrogenase reaction and the reaction rate was strongly affected by the environmental parameters such as pH and temperature. Enzyme immobilization was conducted to improve the enzyme stability during the capture process. By simply adsorbing enzyme on the surface of mesoporous silica foam, enzyme stability against temperature, pH and shear stress was improved. The immobilization process can be completed in 5 mins, and 0.87 U enzyme activity was kept for each gram of immobilization material. After 10 cycles, more than 50 percent of enzyme activity remained. The reusability and improved stability made immobilized ICDH a better candidate for large-scale application of carbon capture

Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans

Background: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliability of our hybrid model. Methods: We used the ARIMA, NARNN and ARIMA-NARNN models to fit and forecast the annual prevalence of schistosomiasis. The modeling time range included was the annual prevalence from 1956 to 2008 while the testing time range included was from 2009 to 2012. The mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the model performance. We reconstructed the hybrid model to forecast the annual prevalence from 2013 to 2016. Results: The modeling and testing errors generated by the ARIMA-NARNN model were lower than those obtained from either the single ARIMA or NARNN models. The predicted annual prevalence from 2013 to 2016 demonstrated an initial decreasing trend, followed by an increase. Conclusions: The ARIMA-NARNN model can be well applied to analyze surveillance data for early warning systems for the control and elimination of schistosomiasis

Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM

Abstract The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil

Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts

10.1145/3017429ACM Transactions on Information Systems35