Recently, algae biocrude has drawn considerable attention as algae are considered to be one of the major fuel feedstocks of the future. Based on some impressive results achieved under appropriate conditions, the algae hydrothermal liquefaction (HTL) process has proven to be energy efficient. However, the HTL of biocrude is characterized by a high nitrogen content, which prevents its use in the field of transportation due to the associated nitrogen oxide emissions. Despite this toxicity, few research efforts have focused on the denitrogenation of algae biocrude. In this study, we review the effect of different strain-specific operation parameters and process upgrades with respect to the nitrogen content of biocrude. To achieve denitrogenation, chemical engineering may be required, although some improvements in biocrude properties have been achieved in a number of process upgrades. The use of similar successful pathways has the potential to improve the field of HTL biocrude denitrogenation. These methods, including the adsorptive and extractive denitrogenations of fossil fuels and the hydrodenitrogenation of the main nitrogen compounds, are helpful for developing a better understanding of the potential of denitrogenation for algae HTL biocrude. We also recommend the use of some available catalysts and corresponding operation parameters to promote continued research on denitrogenation.
In order to assess the capacity of Aquabacterium parvum sp. strain B6 for nitrate-dependent Fe(II) oxidation, batch cultivation was conducted, and its ability to oxidize Fe(II) coupled to nitrate reduction in the presence of diverse organic substrates was studied. Meanwhile, the nitrate-removal rate of B6 with various impact factors was further optimized by the response surface methodology (RSM). The results show that strain B6 is capable of utilizing different organic compounds as substrates for nitrate reduction. Compared with yeast extract, B6 showed a greater potential of chemical oxygen demand (COD) degradation and cell proliferation with acetate and glucose mediums, respectively, while citrate was not beneficial for this process due to its low consumption rate. RSM analysis demonstrated that the maximum nitrate-reduction rate of 30.64% could be achieved with an initial pH of 7.4, incubation temperature of 25.0 °C, and carbon source concentration of 266.10 mg/L.
Biochanin A (BCA), the most abundant isoflavone in chickpeas, presents a wide range of biological activities, such as hypolipidaemic, anti-oxidative, anti-proliferative, and estrogen-like effects. We investigated the interaction between BCA and human serum albumin (HSA) via several techniques. UV–Vis absorption spectroscopy verified the conformational variation of HSA after BCA addition, and fluorescence spectroscopy revealed the relevant binding parameters. Circular dichroism spectroscopy was used to estimate the secondary structural changes of HSA with and without BCA. Molecular docking and dynamics simulations were then applied to study the characteristics of HSA with BCA. Energy decomposition analysis was used to prove that Trp214 in subdomain IIA of HSA is the most likely binding site of BCA. Van der Waals forces and hydrophobic interactions may play important roles during the binding process. All of our results showed that BCA presents significant binding affinity to HSA, thus confirming that the role of HSA has as an efficient transporter of biomolecules.
A great amount of foodborne pathogens were Gram-positive (G+) bacteria, a threat to public health. In this study, considering the binding ability of nisin towards G+ bacteria and the stable fluorescent ability of EGFP protein, a fluorescent nisin–EGFP protein probe was constructed by a gene engineering method. Nisin and EGFP were used as the receptor and fluorophore, respectively, to detect G+ bacteria. The nisin and egfp gene were amplified separately according to the sequence published in GenBank using unique primers. The two genes were cloned into a pET-28b(+) vector resulting in a pET-28b(+)–nisin–egfp vector. The vector was transferred into Escherichia coli (E. coli) BL21 (DE3) for expression. The expressed protein was extracted, purified by a Ni–NTA column, and then tested by the SDS-PAGE method to confirm its molecular weight. Listeria monocytogenes (L. monocytogenes), Staphylococcus aureus (S. aureus), and Micrococcus luteus (M. luteus) were used as the representations of G+ bacteria. E. coli O157, representing the gram-negative (G−) bacteria, was used as a negative control. The binding specificity of the recombinant protein was performed on two types of bacteria and then detected through fluorescent microscopy. The results indicated that the nisin–EGFP probe could detect G+ bacteria at 108 CFU/mL.
Biochar is a potential carrier for nutrients due to its porous nature and abundant functional groups. However, raw biochar has a limited or even negative capacity to adsorb phosphate. To enhance phosphate removal and reduce phosphate releases, acidic, alkaline, and surfactant pretreatments, followed by granulation and ferric oxide loading, were applied to raw biochar powder (Bp). The alkaline pretreatment proved to be the most effective method and exhibited significant pore expansion and surface oxidation. Bg-OH-FO showed the highest phosphate removal efficiency at 99.2% (initial phosphate concentration of 20 mg/L) after granulation and ferric oxide loading. Static adsorption results indicated that a pH value of 4 was the most suitable for phosphate adsorption because of the surface properties of Bg-OH-FO and the distribution of P (V) in water. Higher temperatures and a larger initial phosphate concentration led to better adsorption; the adsorption capacity of Bg-OH-FO was 1.91 mg/g at 313 K with an initial phosphate concentration of 50 mg/L. The Bg-OH-FO adsorption process was endothermic in nature. The Freundlich model seemed to be the optimum isotherm model for Bg-OH-FO. Under continuous adsorption, the flow rate and bed depth were changed to optimize the operation conditions. The results indicate that a slow flow rate and high bed depth helped increase the removal efficiency (η) of the fixed bed. The breakthrough curves fitted well with the Yoon–Nelson model.
Effectively and accurately modelling the spatial relation of fracture surfaces is crucial in the design and construction of large hydropower dams having a complex underlying geology. However, fracture surfaces are randomly formed and vary greatly with respect to their spatial distribution, which makes the construction of accurate 3-D models challenging. In this study, we use an optimal Monte Carlo simulation and dynamic conditioning to construct a fracture network model. We found the optimal Monte Carlo simulation to effectively reduce the error associated with the Monte Carlo method and use dynamic conditioning to ensure the consistency of the model with the actual distribution of fractures on the excavation faces and outcrops. We applied this novel approach to a hydropower station on the Jinshajiang River, China. The simulation results matched the real sampled values well, confirming that the model is capable of effectively and accurately simulating the spatial relations in a fracture network.
The seismic performance of four short concrete columns was investigated under low cycle and repeated loads, including the failure characteristics, hysteretic behavior, rigidity degeneracy and steel-bar stress. The influences of reinforcement strength, stirrup ratio and shear span ratio were also compared. Test results reveal that the restriction effect of stirrups can improve the peak stress, so the bearing capacity of specimen can be improved; for the high-strength short concrete column with high-strength stirrups, it was more reasonable to use ultimate displacement angle to reflect the ductility of the specimen, and the yield strength of high-strength stirrups should be devalued when calculating the stirrup characteristic value; the seismic performance of short column would be improved with the increase of volume–stirrup ratio and shear span ratio; the high-strength stirrups and high-strength longitudinal reinforcements did not yield when the load acting on the specimen reached the peak value, which brought adequate safety stock to these short columns.
Compared with urban floods, dam-break floods are associated with greater uncertainties, including variable dam-break modes and hydrological characteristics, so conventional flood estimation methods cannot be directly applied in the estimation of dam-break flood loss. In particular, there is scant information regarding the conditions of affected area and hydrological characteristics in southwest China. In this paper, we introduce an integrated model for estimating flood loss that is adapted to the mountainous regions of southwestern China in light of the relative lack of available information. This model has three major components: a basic information model, a dam-routed flood propagation simulation model, and a loss estimation model. We established the basic information model despite the relative lack of available information using 3S technology [remote sensing (RS); geographical information system (GIS); global positioning system (GPS)], data mining technology, and statistical analysis techniques. Our dam-routed flood propagation simulation model consists of major hydrologic processes and their governing equations for flow propagation, which we solve using finite-difference schemes. In this model, the flood propagation area is divided into grids and each grid is determined by the characteristic parameters obtained from the propagation simulation. We present a case study of the Lianghekou hydropower station in Sichuan Province, China to illustrate the practical application of this integrated model for life loss estimation.
A multi-objective optimization of non-uniform beams is presented for minimum radiated sound power and weight. The transfer matrix method is used to compute the structural and acoustic responses of a non-uniform beam accurately and efficiently. The multi-objective particle swarm optimization technique is applied to search the Pareto optimal solutions that represent various compromises between weight and sound radiation. Several constraints are imposed, which substantially reduce the volume fraction of feasible solutions in the design space. Two non-uniform beams with different boundary conditions are studied to demonstrate the multi-objective optimal designs of the structure.
In this paper, an automotive engine phase signal simulation algorithm is proposed based on a closed-loop feedback strategy, and its corresponding model is built. The signal incentives are carried out in the front-end, and the synchronization capture and comparison are conducted in the back-end. The phase simulation of signal output is achieved using closed-loop strategy, which can effectively eliminate the inconsistency between crankshaft and camshaft phases, and thus the accuracy and flexibility of phase signal generation are guaranteed. Experimental results show that the proposed algorithm is real time, and the deviation of simulated signals from actual phase signals is small.