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For improving the corrosion resistance of the epoxy coating in 3.5%NaCl solution and extending the service life of the metal， the ZrO2-Cnf was prepared by the hybridization of nano-ZrO2 and carbon fiber (Cnf) with silane coupling agent KH560.Moreover， the ZrO2/EP coatings and ZrO2-Cnf /EP coatings were prepared by spraying method by adding 1%， 2%， 3%and 4%(atomic fraction) of ZrO2 and ZrO2-Cnf fillers into epoxy (EP) coatings， respectively.The modified fillers and modified epoxy composite coatings were characterized by scanning electron microscopy， Fourier transform infrared spectroscopy， electrochemical tests， Vickers hardness tests and friction and wear tests.Results showed that modified fillers could completely improve the corrosion resistance of epoxy resin coatings.When the content of filler was 2%， the corrosion resistance of ZrO2/EP coating and ZrO2-Cnf /EP coating was the best， and the wear loss was the smallest.When the content of the two fillers was 3%， the maximum hardness values were 32.9 HV5.0 and 46.6 HV5.0， respectively.

Career decision-making self-efficacy is a key factor influencing high school students' ability to make informed choices. It is closely associated with their professional interests, learning engagement, and academic performance. This study aims to explore the latent categories of career decision-making self-efficacy among Chinese high school students and analyze the differences in learning engagement across students with different types of career decision-making self-efficacy. A convenience sampling method was employed to recruit 510 Chinese high school students as participants. A questionnaire survey was conducted using the Career Decision-Making Self-Efficacy Scale and the Learning Engagement Scale. The validity of the questionnaire was analyzed using Amos 23.0, descriptive statistics and correlation analyses were performed with SPSS 26.0, and a latent profile model was constructed using Mplus 8.0. The results indicate that there are four latent categories of career decision-making self-efficacy among high school students. In terms of learning engagement levels, the categories are ranked from highest to lowest as follows: high career decision-making self-efficacy type, lack of external exploration type, lack of internal exploration type, and low career decision-making self-efficacy type. Students with high and low career decision-making self-efficacy demonstrated significantly higher levels of learning engagement compared to those categorized as lacking external or internal exploration. Therefore, the design of career education curricula for high school students should focus on enhancing career decision-making self-efficacy to stimulate their intrinsic motivation for learning. Differences among various student types should be acknowledged, allowing for tailored and individualized instruction. Additionally, efforts should be made to strengthen integrated career guidance that links academics, career interests, and future professions, guiding all stakeholders to shift away from entrenched practices of "exam-oriented education" and utilitarian perspectives. [ABSTRACT FROM AUTHOR]

Constructing heterojunctions is an effective strategy for improving the migration of electronic charge carriers and enhancing electronic conductivity. Herein, polyvinylpyrrolidone crosslinked with graphene oxide was used as a template to construct a FeTiO3@Fe2TiO5 endogenous heterojunction anode material (hetero-FTO) anode. The initial electrochemical capacity of the hetero-FTO anode (1207 mA h g−1 at 100 mA g−1) was approximately twice that of FTO (600 mA h g−1 at 100 mA g−1). Electrochemical kinetics and density functional theory calculations demonstrated that the built-in electric field formed at the interface of the endogenous heterojunction increased the electronic conductivity and effectively improved the conversion rate. The structural evolution of the heterojunction during cycling was tracked using in situ XPS and ex situ HRTEM and calculation of Gibbs free energies. After 100 cycles, the FeTiO3@Fe2TiO5 heterojunction structures transformed into cubic phase γ-Fe2O3; however, the capacity still increased to 865 mA h g−1. This ingenious heterogeneous-structure-design strategy and analysis of the heterogeneous structural evolution are crucial for improving the lithium-storage performance of batteries, especially those containing titanium-based conversion-type anode materials. [ABSTRACT FROM AUTHOR]

In order to study the selection of coping strategies for the manufacturer facing different supply interruption risks, this paper constructs a supply chain consisting of one manufacturer and one supplier and uses no-taking coping strategies as the benchmark model to analyze the resilience of supply chain formed by the manufacturer's adoption of penalty mechanism, emergency supplier mechanism, and strategic investment mechanism. The research shows that in the face of various levels of supply interruption risk, the manufacturer adopting a strategic investment mechanism will achieve high resilience, enabling the manufacturer and supplier to achieve mutual benefit and win-win results. In some cases of high interruption risk, the manufacturer adopting an emergency supplier mechanism can achieve higher chain resilience compared with not taking emergency measures, but its ability to improve supply chain resilience is weaker than that of a strategic investment mechanism. The penalty mechanism is applicable to situations where some interruption risk is characterized by low risk, and in such cases, both the penalty mechanism and the strategic investment mechanism can enhance the resilience of the supply chain. [ABSTRACT FROM AUTHOR]

We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete Fourier transform (DFT) to extract fifteen features from vibration signals in the time and frequency domains of four bearing failure forms, which addresses the issue of ambiguous fault identification caused by their nonlinearity and nonstationarity. The extracted feature vectors are then divided into training and test sets as SVM inputs for fault diagnosis. To optimize the SVM, we construct a hybrid kernel SVM using a polynomial kernel function and radial basis kernel function. BO is used to optimize the extreme values of the objective function and determine their weight coefficients. We create an objective function for the Gaussian regression process of BO using training and test data as inputs, respectively. The optimized parameters are used to rebuild the SVM, which is then trained for network classification prediction. We tested the proposed diagnostic model using the bearing dataset of the Case Western Reserve University. The verification results show that the fault diagnosis accuracy is improved from 85% to 100% compared with the direct input of vibration signal into the SVM, and the effect is significant. Compared with other diagnostic models, our Bayesian-optimized hybrid kernel SVM model has the highest accuracy. In laboratory verification, we took sixty sets of sample values for each of the four failure forms measured in the experiment, and the verification process was repeated. The experimental results showed that the accuracy of the Bayesian-optimized hybrid kernel SVM reached 100%, and the accuracy of five replicates reached 96.7%. These results demonstrate the feasibility and superiority of our proposed method for fault diagnosis in rolling bearings. [ABSTRACT FROM AUTHOR]

Many companies have captured and analyzed huge volumes of data to improve the decision mechanism of supply chain, this paper presents a big data harvest model that uses big data as inputs to make more informed decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates foods demand into processes and divides processes into tasks and assets is presented, and an example of how big data in the food supply chain can be combined with Bayesian network and deduction graph model to guide production decision. Our conclusions indicate that the decision-making mechanism has vast potential by extracting value from big data.

Ferrous titanate (FeTiO3) has a high theoretical capacity and physical and chemical properties stability, so it is a potential lithium anode material. In this study, FeTiO3 nanopowder and nanosheets were prepared by the sol–gel method and the hydrothermal method. In addition, niobium-ion doping was carried out, the radius of Nb close to Ti so the Nb can easily enter into the FeTiO3 lattice. Nb can provide more free electrons to improve the electrochemical performance. Then, the effects of the morphology and niobium doping on the microstructure and electrochemical properties of FeTiO3 were systematically studied. The results show that FeTiO3 nanosheets have a better lithium storage performance than nanopowders because of its high specific surface area. A certain amount of niobium doping can improve the electrochemical performance of FeTiO3. Finally, a 1 mol% niobium-doping FeTiO3 nanosheets (1Nb-FTO-S) electrode provided a higher specific capacity of 782.1 mAh g−1 at 50 mA g−1. After 200 cycles, the specific capacity of the 1Nb-FTO-S electrode remained at 509.6 mAh g−1. It is revealed that an increased specific surface area and ion doping are effective means to change the performance of lithium, and the proposed method looks promising for the design of other inorganic oxide electrode materials. [ABSTRACT FROM AUTHOR]

In recent years, return freight insurance (RFI) has emerged as a solution to the problem of returns of goods purchased online. However, although RFI reduces the return costs of both parties and increases the purchase intention of consumers, it also increases the rate of returns and reduces retailers' profits. Therefore, some online retailers have looked at increasing their service effort as a means of improving the service level and reducing the rate of returns. Considering the impact of retailers' service efforts on consumer returns, the retailers' choice of RFI strategy is very important for its profit. It is worth studying how retailers choose RFI policies and the pricing and service effort level in different market environments. In this study, we examine the retailers' RFI decision-making process, including the influence of retail service effort on consumer returns, by developing three duopolistic-competition game models based on three RFI markets. In this case, we analyze and compare the retailers' optimal pricing decisions, optimal service effort decisions, and optimal profits in each RFI market, and identify the relationship between the retailers' optimal decisions and the degree of competition. The result shows that under the market where RFI is provided by the retailer, the retailers' optimal pricing and optimal service effort level both increase with the increase of market competition. In addition, retailers should consider the impact of market competition and return compensation on consumer demand when making the decision of whether to offer freight insurance. [ABSTRACT FROM AUTHOR]

A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was proposed to solve the unclear fault characterization of rolling bearing vibration signal due to its nonlinear and nonstationary characteristics. A whale gray wolf optimization algorithm (WGWOA) was proposed by combining whale optimization algorithm (WOA) and gray wolf optimization (GWO), and the rolling bearing signal was decomposed by using variational mode decomposition (VMD). Each eigenvalue was extracted as eigenvector after VMD, and the training and test sets of the fault diagnosis model were divided accordingly. The support vector machine (SVM) was used as the fault diagnosis model and optimized by using WGWOA. The validity of this method was verified by two cases of Case Western Reserve University bearing data set and laboratory test. The test results show that in the bearing data set of Case Western Reserve University, compared with the existing VMD-SVM method, the fault diagnosis accuracy rate of the WGWOA-VMD-SVM method in five repeated tests reaches 100.00%, which preliminarily verifies the feasibility of this algorithm. In the laboratory test case, the diagnostic effect of the proposed fault diagnosis method is compared with backpropagation neural network, SVM, VMD-SVM, WOA-VMD-SVM, GWO-VMD-SVM, and WGWOA-VMD-SVM. Test results show that the accuracy rate of WGWOA-VMD-SVM fault diagnosis is the highest, the accuracy rate of a single test reaches 100.00%, and the accuracy rate of five repeated tests reaches 99.75%, which is the highest compared with the above six methods. WGWOA plays a good optimization role in optimizing VMD and SVM. The signal decomposed by VMD is optimized by using the WGWOA algorithm without mode overlap. WGWOA has the better convergence performance than WOA and GWO, which further verifies its superiority among the compared methods. The research results can provide an effective improvement method for the existing rolling bearing fault diagnosis technology. [ABSTRACT FROM AUTHOR]

The severe volumetric changes occur during the lithiation/de-lithiation of silicon materials, which are the main cause of battery capacity failure. In this study, the expansion behavior of a cell composed of a silicon-carbon anode and Li(Ni 0.5 Co 0.2 Mn 0.3)O 2 (NCM523) was measured using the electrochemical dilatometry, and the contributions of different silicon and carbon components to the expansion were analyzed, along with factors affecting the cyclic stability of the silicon carbon anode. The results indicate that amorphous carbon can inhibit the volume expansion of monocrystalline silicon in the late stage of lithiation, thereby ensuring the cyclic stability of silicon. The cyclic stability of silicon-carbon composites is affected by irreversible expansion and expansion variation, and these two factors are negatively correlated. This research provides insights and guidance for the design of silicon carbon electrodes with superior electrochemical performance. • The impact of silicon-carbon components on cycle stability. • The depth of lithiation influences the expansion of the anode. • Amorphous carbon can effectively inhibit the expansion of silicon anode. • The change in expansion is negatively correlated with irreversible expansion. [ABSTRACT FROM AUTHOR]