Food Science and Biotechnology - This study aims to investigate antioxidative and antibacterial properties of fresh garlic (non-aged, NG) and aged garlic (AG) by-products extracted with distilled... 相似文献
This study investigated the external operational factors that would reduce the thermodynamic constrains preventing the simultaneous achievement of high hydrogen productivities (HPs) and hydrogen yields (HYs) in the bioreactor. At hydraulic retention time (HRT) of 1, the maximum HPs and HYs achieved was 35 L H2/h and 3.91 mol H2/mol glucose, respectively. At this stage, the bacterial granules occupied approximately 75% of the bioreactor and consisted of the settled biomass density of 40.6 g/L (settled granule bed height = 13.8 cm). The formation of bacterial granules improved the bioreactor performance and resulted in higher substrate conversion efficiency (95%), nutrient influent (7.5 L/h) and de-gassed effluent recycle rates (3.5 L/min). In conclusion, this study demonstrated that high nutrient influent and high de-gassed effluent recycle rates reduced the thermodynamic constrains preventing the achievement of higher H2 productivities in the bioreactor system. 相似文献
Water Resources Management - Accurate prediction of shear stress distribution along the boundary in an open channel is the key to solving numerous critical engineering problems such as flood... 相似文献
As the only fuel that is not chemically bound to carbon, hydrogen has gained interest as an energy carrier to face the current environmental issues of greenhouse gas emissions and to substitute the depleting non-renewable reserves. In the last years, there has been a significant increase in the number of publications about the bacterium Thermotoga neapolitana that is responsible for production yields of H2 that are among the highest achievements reported in the literature. Here we present an extensive overview of the most recent studies on this hyperthermophilic bacterium together with a critical discussion of the potential of fermentative production by this bacterium. The review article is organized into sections focused on biochemical, microbiological and technical issues, including the effect of substrate, reactor type, gas sparging, temperature, pH, hydraulic retention time and organic loading parameters on rate and yield of gas production. 相似文献
This paper investigates the combined effect of actuator saturation and time-delay on load frequency control (LFC) of a wind-integrated power system (WIPS). Actuator saturation is represented in two different approaches such as polytopic and sector bounding. Delay-discretization-based sliding mode \(H_{\infty }\) control approach is proposed to design a novel LFC scheme. The proposed control scheme requires present as well as delayed states information as input to the controller. This requirement of control scheme is fulfilled by adopting a finite known delay. This finite known delay used in controller design is discretized into delay intervals. Lyapunov–Krasovskii functional is defined for each delay interval, and \(H_{\infty }\) stabilization criteria for the closed loop WIPS are derived in linear matrix inequality framework using Wirtinger-based inequality. The proposed control scheme is tested by considering a numerical example of two-area WIPS.
Bioleaching studies for chalcopyrite contained ball mill spillages are very scarce in the literature. We developed a process flow sheet for the recovery of copper metal from surface activated (600 °C, 15 min) ball mill spillage through bio-hydrometallurgical processing route. Bioleaching of the activated sample using a mixed meso-acidophilic bacterial consortium predominantly A. ferrooxidans strains was found to be effective at a lixiviant flow rate of 1.5 L/h, enabling a maximum 72.36% copper recovery in 20 days. Mineralogical as well as morphological changes over the sample surface were seen to trigger the bioleaching efficiency of meso-acidophiles, thereby contributing towards an enhanced copper recovery from the ball mill spillage. The bio-leach liquor containing 1.84 g/L Cu was purified through solvent extraction using LIX 84I in kerosene prior to the recovery of copper metal by electrowinning. Purity of the copper produced through this process was 99.99%. 相似文献
The main goal of this study is to assess and compare three advanced machine learning techniques, namely, kernel logistic regression (KLR), naïve Bayes (NB), and radial basis function network (RBFNetwork) models for landslide susceptibility modeling in Long County, China. First, a total of 171 landslide locations were identified within the study area using historical reports, aerial photographs, and extensive field surveys. All the landslides were randomly separated into two parts with a ratio of 70/30 for training and validation purposes. Second, 12 landslide conditioning factors were prepared for landslide susceptibility modeling, including slope aspect, slope angle, plan curvature, profile curvature, elevation, distance to faults, distance to rivers, distance to roads, lithology, NDVI (normalized difference vegetation index), land use, and rainfall. Third, the correlations between the conditioning factors and the occurrence of landslides were analyzed using normalized frequency ratios. A multicollinearity analysis of the landslide conditioning factors was carried out using tolerances and variance inflation factor (VIF) methods. Feature selection was performed using the chi-squared statistic with a 10-fold cross-validation technique to assess the predictive capabilities of the landslide conditioning factors. Then, the landslide conditioning factors with null predictive ability were excluded in order to optimize the landslide models. Finally, the trained KLR, NB, and RBFNetwork models were used to construct landslide susceptibility maps. The receiver operating characteristics (ROC) curve, the area under the curve (AUC), and several statistical measures, such as accuracy (ACC), F-measure, mean absolute error (MAE), and root mean squared error (RMSE), were used for the assessment, validation, and comparison of the resulting models in order to choose the best model in this study. The validation results show that all three models exhibit reasonably good performance, and the KLR model exhibits the most stable and best performance. The KLR model, which has a success rate of 0.847 and a prediction rate of 0.749, is a promising technique for landslide susceptibility mapping. Given the outcomes of the study, all three models could be used efficiently for landslide susceptibility analysis.