Search

In this work, the functional groups of Eurohypnum leptothallumextract (ELE) were extracted by aqueous immersion and identified by FTIR. The corrosion inhibitory effect of ELE as a natural plant corrosion inhibitor on pure iron in 0.5 mol L−1H2SO4solution was investigated by test methods such as the weight loss method, electrochemical behaviour and detection of metal surface topography. The results show that ELE has a positive inhibitory effect on the corrosion behaviour of pure iron in 0.5 mol L−1H2SO4solution, and the higher the concentration of ELE, the greater the corrosion inhibitory effect. It can still reach 83.97 % at high temperatures. The results of SEM examination and contact angle measurements show that the corrosion degree of the metal decreases significantly after the additon of ELE and that the hydrophobicity of the metal surface increases. The adsorption of ELE on the surface of pure iron tends to isothermal Langmuir adsorption and, as a mixed corrosion inhibitor, the charge transfer resistance of the system increases significantly and the capacitance value of the electrical double layer decreases significantly.

The relationship between spatial heterogeneity and students' academic performance is a widely researched topic. This study extends the concept of spatial heterogeneity into two categories - allocatable (acquired after birth) and ascribed (determined before birth) - using seating and hometown information as variables in Spatial Durbin Models for statistical analysis, identifying seating as the salient feature. Subsequently, through 2,000 iterations of random state testing with undergraduate data from two classes (N=282), our research compares six representation learning methods, including an improved, custom version of attention-based Graphic Convolutional Network, affirming the superior efficacy of our enhanced approach in extracting seating features. By doing so, our study broadens the application scenarios of social comparison theory and group dynamics theory, while also providing a feasible best-practice reference for network-based instructional modeling.

This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a four-quadrant clustering technique. The AIM model delineates student investment into four quadrants based on their time and energy commitment to academic pursuits, distinguishing between result-oriented and process-oriented investments. The findings reveal that the four-quadrant method surpasses machine learning clustering in predictive accuracy, highlighting the robustness of manual feature engineering. The study's significance lies in its potential to guide educators in designing targeted interventions and personalized learning strategies, emphasizing the importance of process-oriented assessment in education. Future research is recommended to expand the sample size and explore the integration of deep learning models for validation.

This research focuses on the attitudes of potential consumers towards generative artificial intelligence (GenAI) advertisements, employing a multi-experimental approach based on engagement to shed light on how e-marketers should leverage novel technological tools in the age of human-AI co-creation to enhance brand favorability. The experimental findings indicate the continued adaptiveness of concepts such as in-group bias, IKEA effect, and social identity theory in the GenAI era, demonstrating that (a) consumers' awareness of AI authorship (b) their level of participation in the co-creative process and (c) their perceived authenticity, significantly influence their attitudes. This study expands the boundaries of theories previously confined to human populations and provides pioneering practical guidance for AI co-creation in the realm of electronic commerce.

Silicon (Si) treatment has been shown to reduce the toxicity and accumulation of lead (Pb) in many plants, including rice. The mechanisms responsible for this effect are poorly understood. We investigated the effects of Si treatment on Pb toxicity and accumulation in two rice mutants (lsi1and lsi2) defective in Si uptake and in their wild types. Si did not alleviate Pb-induced inhibition of root elongation in short-term experiments, but reduced Pb accumulation in wild types, but not in mutants, in long-term experiments. Pre-treatment with Si reduced Pb concentration in xylem sap and Pb accumulation in wild types but not in mutants. In split-root experiments, Si treatment reduced Pb accumulation but did not alter Pb localization in roots. Si treatment suppressed the expression of many genes encoding proteins that may participate in Pb uptake and transport in the wild type, but not in the lsi1mutant. These results indicate that Si accumulation in shoots is required to reduce Pb uptake in rice and that the effect is achieved via Si-induced suppression of genes encoding proteins involved in Pb uptake and/or transport.