As China is faced with the double dilemmas of environmental pollution and energy security, new-energy vehicles (NEVs) come with high expectations, which need to be guided by an “invisible hand”. To ...analyse the optimal functioning power of policies and determine the direction of future policy implementation, this paper utilizes the COPA framework (i.e., analysis from four dimensions of contents, outlook, power, and authorities) to analyse policy evolution in respect of the new-energy vehicle industry (NEVI). In addition, a quantitative table of policy power is designed to construct the policy effects in various periods. Furthermore, this paper employs threshold model and quantile regression model to explore the threshold effect of policy power on the policy implementation effects and the transformation of policy implementation effects at different development stages, respectively. The results are as follows. (1) The Chinese NEVI policy continues to attach importance to government-guided consumption and government-supported technical development, with the major issuing form still being “notices”. Although “moderate” industrial policies are adopted as the main policies, the issuance strength has been rising periodically, and the functioning strength has been maintaining a steady rise year by year. The non-definition of the competent authorities is one of the key factors that affect the development of the NEVI. (2) The policy power has a significant threshold effect on its functioning strength. When the policy strength exceeds the threshold value of 69, the effect of the policy will nearly double; thus, to promote the technological innovation of NEVs, it is necessary to formulate high-intensity policies. (3) The effect of industrial policy will differ greatly at different development stages. Along with the gradual formation of market orientation of the NEVI, the effect of industrial policies has weakened gradually. Properly reducing the subsidy of NEVs will achieve the optimal allocation of government resources.
•Policy evolution of China NEVI is analysed based on COPA framework.•A threshold model is employed to explore the threshold effect of policy power on the policy implementation.•A quantile regression model is utilized to investigate the transformation of policy implementation effects.•It is necessary to formulate high-power policies to promote the process of technological innovation of NEVI.•Reducing the subsidy intensity of NEVI will achieve the optimal allocation of government resources.
Potassium-ion batteries (PIBs) have attracted tremendous attention due to their low cost, fast ionic conductivity in electrolyte, and high operating voltage. Research on PIBs is still in its infancy, ...however, and achieving a general understanding of the drawbacks of each component and proposing research strategies for overcoming these problems are crucial for the exploration of suitable electrode materials/electrolytes and the establishment of electrode/cell assembly technologies for further development of PIBs. In this review, we summarize our current understanding in this field, classify and highlight the design strategies for addressing the key issues in the research on PIBs, and propose possible pathways for the future development of PIBs toward practical applications. The strategies and perspectives summarized in this review aim to provide practical guidance for an increasing number of researchers to explore next-generation and high-performance PIBs, and the methodology may also be applicable to developing other energy storage systems.
Oral English teaching is an important form of cultivating students' English accomplishment and improving their English learning effect. In the context of intelligent education, by giving full play to ...the advantages of computer network and actively reconstructing the new mode of Oral English teaching, we will, on the basis of optimizing the form of oral English teaching and by integrating high-quality oral English teaching resources, to promote students to participate in oral English learning and speaking practice in a conscious and spontaneous way. Based on the analysis of the existing problems in spoken English teaching, this paper puts forward the construction and implementation of a new spoken English teaching model based on computer network.
Potassium‐ion batteries (PIBs) are promising energy storage systems because of the abundance and low cost of potassium. The formidable challenge is to develop suitable electrode materials and ...electrolytes for accommodating the relatively large size and high activity of potassium. Herein, Bi‐based materials are reported as novel anodes for PIBs. Nanostructural design and proper selection of the electrolyte salt have been used to achieve excellent cycling performance. It is found that the potassiation of Bi undergoes a solid‐solution reaction, followed by two typical two‐phase reactions, corresponding to Bi ↔ Bi(K) and Bi(K) ↔ K5Bi4 ↔ K3Bi, respectively. By choosing potassium bis(fluorosulfonyl)imide (KFSI) to replace potassium hexafluorophosphate (KPF6) in carbonate electrolyte, a more stable solid electrolyte interphase layer is achieved and results in notably enhanced electrochemical performance. More importantly, the KFSI salt is very versatile and can significantly promote the electrochemical performance of other alloy‐based anode materials, such as Sn and Sb.
Bismuth stores potassium electrochemically via a solid‐solution reaction, followed by two typical two‐phase reactions, corresponding to Bi↔ Bi(K) and Bi(K) ↔ K5Bi4 ↔ K3Bi, respectively. Moreover, a more uniform, stable, conductive, and robust solid electrolyte interphase is achieved by replacing potassium hexafluorophosphate with potassium bis(fluorosulfonyl)imide (KFSI) and hence results in better cycling performance. The KFSI salt is also effective in other alloy‐based anode materials, such as Sn and Sb.
Earth-abundant potassium is a promising alternative to lithium in rechargeable batteries, but a pivotal limitation of potassium-ion batteries is their relatively low capacity and poor cycling ...stability. Here, a high-performance potassium-ion battery is achieved by employing few-layered antimony sulfide/carbon sheet composite anode fabricated via one-step high-shear exfoliation in ethanol/water solvent. Antimony sulfide with few-layered structure minimizes the volume expansion during potassiation and shortens the ion transport pathways, thus enhancing the rate capability; while carbon sheets in the composite provide electrical conductivity and maintain the electrode cycling stability by trapping the inevitable by-product, elemental sulfur. Meanwhile, the effect of the exfoliation solvent on the fabrication of two-dimensional antimony sulfide/carbon is also investigated. It is found that water facilitates the exfoliation by lower diffusion barrier along the 010 direction of antimony sulfide, while ethanol in the solvent acts as the carbon source for in situ carbonization.
•Three types of treatments were used and three treatment strategies were also determined.•Treatments were very costly and costs were very sensitive to treatment types used and timing of treatments ...conducted.•Strategically treating fish at the early state was more economic than at later stage.•Bath treatment had higher costs than wrasse and in-feed treatments.•Wrasse is a better option economically and ecologically, but cannot generate instantaneous reduction in sea lice level.
This paper explores the costs of sea lice control strategies associated with salmon aquaculture at a farm level in Norway. Diseases can cause reduction in growth, low feed efficiency and market prices, increasing mortality rates, and expenditures on prevention and treatment measures. Aquaculture farms suffer the most direct and immediate economic losses from diseases. The goal of a control strategy is to minimize the total disease costs, including biological losses, and treatment costs while to maximize overall profit. Prevention and control strategies are required to eliminate or minimize the disease, while cost-effective disease control strategies at the fish farm level are designed to reduce the losses, and to enhance productivity and profitability. Thus, the goal can be achieved by integrating models of fish growth, sea lice dynamics and economic factors. A production function is first constructed to incorporate the effects of sea lice on production at a farm level, followed by a detailed cost analysis of several prevention and treatment strategies associated with sea lice in Norway. The results reveal that treatments are costly and treatment costs are very sensitive to treatment types used and timing of the treatment conducted. Applying treatment at an early growth stage is more economical than at a later stage.
We developed an ultrasensitive fluorescence resonance energy transfer (FRET) aptasensor for kanamycin detection, using upconversion nanoparticles (UCNPs) as the energy donor and graphene as the ...energy acceptor. Oleic acid modified upconversion nanoparticles were synthesized through a hydrothermal process followed by a ligand exchange with hexanedioic acid. The kanamycin aptamer (5'-NH2-AGATGGGGGTTGAGGCTAAGCCGA-3') was tagged to UCNPs through an EDC–NHS protocol. The π–π stacking interaction between the aptamer and graphene brought UCNPs and graphene in close proximity and hence initiated the FRET process resulting in quenching of UCNPs fluorescence. The addition of kanamycin to the UCNPs–aptamer–graphene complex caused the fluorescence recovery because of the blocking of the energy transfer, which was induced by the conformation change of aptamer into a hairpin structure. A linear calibration was obtained between the fluorescence intensity and the logarithm of kanamycin concentration in the range from 0.01nM to 3nM in aqueous buffer solution, with a detection limit of 9pM. The aptasensor was also applicable in diluted human serum sample with a linear range from 0.03nM to 3nM and a detection limit of 18pM. The aptasensor showed good specificity towards kanamycin without being disturbed by other antibiotics. The ultrahigh sensitivity and pronounced robustness in complicated sample matrix suggested promising prospect of the aptasensor in practical applications.
•An aptasensor is constructed to detect kanamycin based on upconversion fluorescence resonance energy transfer.•The conformation change of kanamycin aptamer into a hairpin structure after interacting with the target is accompanied by the alteration of energy-transfer efficiency.•The aptasensor for kanamycin detection is ultrasensitive.•The aptasensor is robust in human serum samples indicating its prospect of practical applications.
Due to the abundant potassium resource on the Earth’s crust, researchers now have become interested in exploring high-performance potassium-ion batteries (KIBs). However, the large size of K+ would ...hinder the diffusion of K ions into electrode materials, thus leading to poor energy/power density and cycling performance during the depotassiation/potassiation process. So, few-layered V5S8 nanosheets wrapping a hollow carbon sphere fabricated via a facile hollow carbon template induced method could reversibly accommodate K storage and maintain the structure stability. Hence, the as-obtained V5S8@C electrode enables rapid and reversible storage of K+ with a high specific capacity of 645 mAh/g at 50 mA/g, a high rate capability, and long cycling stability, with 360 and 190 mAh/g achieved after 500 and 1000 cycles at 500 and 2000 mA/g, respectively. The excellent electrochemical performance is superior to the most existing electrode materials. The DFT calculations reveal that V5S8 nanosheets have high electrical conductivity and low energy barriers for K+ intercalation. Furthermore, the reaction mechanism of the V5S8@C electrode in KIBs is probed via the in operando synchrotron X-ray diffraction technique, and it indicates that the V5S8@C electrode undergoes a sequential intercalation (KV5S8) and conversion reactions (K2S3) reversibly during the potassiation process.
The prediction of system degradation is very important as it serves as an important basis for the formulation of condition-based maintenance strategies. An effective health indicator (HI) plays a key ...role in the prediction of system degradation as it enables vital information for critical tasks ranging from fault diagnosis to remaining useful life prediction. To address this issue, a method for monitoring data fusion and health indicator construction based on an autoencoder (AE) and a long short-term memory (LSTM) network is proposed in this study to improve the predictability and effectiveness of health indicators. Firstly, an unsupervised method and overall framework for HI construction is built based on a deep autoencoder and an LSTM neural network. The neural network is trained fully based on the normal operating monitoring data and then the construction error of the AE model is adopted as the health indicator of the system. Secondly, we propose related machine learning techniques for monitoring data processing to overcome the issue of data fusion, such as mutual information for sensor selection and t-distributed stochastic neighbor embedding (T-SNE) for operating condition identification. Thirdly, in order to verify the performance of the proposed method, experiments are conducted based on the CMAPSS dataset and results are compared with algorithms of principal component analysis (PCA) and a vanilla autoencoder model. Result shows that the LSTM-AE model outperforms the PCA and Vanilla-AE model in the metrics of monotonicity, trendability, prognosability, and fitness. Fourthly, in order to analyze the impact of the time step of the LSMT-AE model on HI construction, we construct and analyze the system HI curve under different time steps of 5, 10, 15, 20, and 25 cycles. Finally, the results demonstrate that the proposed method for HI construction can effectively characterize the health state of a system, which is helpful for the development of further failure prognostics and converting the scheduled maintenance into condition-based maintenance.
Recent advances in computer vision and camera-equipped unmanned aerial systems (UAS) for 3D modeling enable UAS-based photogrammetry surveys with high spatial-temporal resolutions. To generate ...consistent and high-quality 3D models using UASs, understanding how influence factors (i.e., flight height, image overlap, etc.) affect the 3D modeling accuracy and their levels of significance are important. However, there is little to no quantitative analysis that studies how these influence factors interact with and affect the accuracy when changing the values of the influence factors. Moreover, there is little to no research that assesses more than three influence factors. Therefore, to fill this gap, this paper aims to evaluate and predict the accuracy generated by different flight combinations. This paper presents a study that (1) assessed the significance levels of five influence factors (flight height, average image quality, image overlap, ground control point (GCP) quantity, and camera focal lengths), (2) investigated how they interact and impact 3D modeling accuracy using the multiple regression (MR) method, and (3) used the developed MR models for predicting horizontal and vertical accuracies. To build the MR model, 160 datasets were created from 40 flight missions collected at a site with a facility and open terrain. For validating the prediction model, five testing datasets were collected and used at a larger site with a complex building and open terrain. The results show that the findings of this study can be applied to surveyors’ better design flight configurations that result in the highest accuracies, given different site conditions and constraints. The results also provide a reasonable prediction of accuracy given different flight configurations.
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