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Students frequently encounter challenges in vocabulary selection, clarity of expression, and the construction of lengthy, under-informed essays during communication and writing tasks. To address these issues, this paper introduces a novel approach utilizing sentence recommendation to enhance students’ communicative and writing competencies. Specifically, the proposed model employs a Probabilistic Latent Semantic Analysis (PLSA) topic model to calculate the similarity of Chinese sentences and recommends contextually relevant sentences to students, thereby guiding their communication and writing efforts. Additionally, the Latent Dirichlet Allocation (LDA) topic model is applied to analyze and mine the corpus at both word and sentence levels, culminating in the creation of comprehensive and varied practice documents through thoughtful integration. Building on the capabilities of these models, we devise a pedagogical strategy for the course “Communication and Writing”. Empirical testing reveals significant improvements; the average score of the experimental class’s pre-test exceeded the post-test by 4.01 points in terms of self-efficacy in communication and writing tasks. Moreover, the total scores reflecting students’ self-efficacy in communication and writing assignments and skills showed marked enhancement, bolstering their self-efficacy in these areas. Regarding behavioral changes, the proportion of students frequently initiating communication and writing activities surged from 4.5% to 23%, an increase of 18.5%. Ultimately, the instructional strategies outlined in this study provided students with effective practice tools, significantly elevating their cognitive and sentence quality in communication and writing tasks.

The stability of NOx concentration in a coal-fired unit affects the operation performance of denitrification system. By constructing the stability evaluation model, the quantitative evaluation of the big data distribution of NOx concentration was realized. The original big data cleaning method combining K-means clustering and 3σ criterion was constructed, and the data of different working conditions were divided by the sliding window method. A NOx concentration reference value model was established based on the least-squares regression method. Based on the deviation degree, the deviation degree function and the stability coefficient function were constructed, and the stability scoring function was obtained after normalization, so as to realize the quantitative evaluation of the stability of full load NOx. The model was used to evaluate NOx data from a 660 MW coal-fired unit. The results show that the overall concentration of NOx concentration distribution is high and positively correlated with load rate. The stability score of variable load condition is about 2.35% lower than that of stable condition. When the load rate is increased from 50% to 100%, the stability score is increased by 21.28%. It shows that the model can effectively evaluate the stability of NOx distribution and provide a basis for benchmarking coal-fired units.

To examine the effects of water washing and acid-based deashing on the structure as well as combustion characteristics of Zhundong lignite, this study used high-speed planar laser-induced fluorescence measurements (OH-PLIF) with a specific burner and characterization techniques including XRD, BET, and ICP-AES as the method. The results indicated that both water washing and deashing can remove the ash and the main mineral alkali metals. Compared with RC, the total amount of OH release from WWC and UCC was increased attributing to the addition of combustibles and volatiles. The ignition of WWC and UCC was faster than that of RC, while the burning rate followed the opposite order. Experimental result confirms that the alkali metal and alkaline earth metals play a catalytic role in coal combustion. Meanwhile, the increase of the BET surface area and the reduction of ash are conducive to heat transfer, which is favorable for the ignition of pulverized coal. [ABSTRACT FROM AUTHOR]