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BackgroundThere are more than 6000 rare diseases in existence today, with the number of patients with these conditions rapidly increasing. Most research to date has focused on the diagnosis, treatment, and development of orphan drugs, while few studies have examined the topics and emotions expressed by patients living with rare diseases on social media platforms, especially in online health communities (OHCs). ObjectiveThis study aimed to determine the topic categorizations and sentiment polarity for albinism in a Chinese OHC, Baidu Tieba, using multiple methods. The OHC was deeply mined using topic mining, social network analysis, and sentiment polarity analysis. Through these methods, we determined the current situation of community construction, identifying the ongoing needs and problems experienced by people with albinism in their daily lives. MethodsWe used the albinism community on the Baidu Tieba platform as the data source in this study. Term frequency–inverse document frequency, latent dirichlet allocation models, and naive Bayes were employed to mine the various topic categories. Social network analysis, which was completed using the Gephi tool, was employed to analyze the evolution of the albinism community. Sentiment polarity analysis was performed using a long short-term memory algorithm. ResultsWe identified 8 main topics discussed in the community: daily sharing, family, interpersonal communication, social life and security, medical care, occupation and education, beauty, and self-care. Among these topics, daily sharing represented the largest proportion of the discussions. From 2012 to 2019, the average degree and clustering coefficient of the albinism community continued to decline, while the network center transferred from core communities to core users. A total of 68.43% of the corpus was emotional, with 35.88% being positive and 32.55% negative. There were statistically significant differences in the distribution of sentiment polarity between topics (P

The soil surface in the southern Xinjiang region has a high salt content, and flooding water causes salt dissolution and pollutes surface water. Therefore, it is particularly important to study the technology of nitrogen and phosphorus removal in the degradation of high salt wastewater. Activated sludge was inoculated in an SBR system with a height to diameter ratio (RH/D) of 7.5, and synthetic wastewater (containing 0.25 mg/L Ni2+) was used as influent to analyze the changes in sludge morphology, pollutant removal performance, microbial community during the sludge granulation process, as well as the ability of granular sludge to remove pollutants from high salt wastewater under salinity stress. The results showed that the mature granular sludge was yellow in multiple forms, with an average particle size of 357 μm. The average removal rates of COD, TP, and NH4+-N in wastewater were 95%,91.27%,and 94.5%, respectively. The dominant bacterial genera were Zoogloea, Flavobacterium,and Unclassified_f_Comamonadaceae. The influent water quality would change the relative abundance of microorganisms, while there was no significant impact on the microbial community structure. When the salt application rate was 15 g/L, the removal rates of COD, TP, and NH4+-N were 86.7%, 67.2%, and 62.6%, respectively. The sludge maintained good carbon removal ability. When the salt application rate exceeded 15 g/L, the removal rates of all indicators showed a downward trend. The application of low concentrations of heavy metals accelerated the start-up of granular sludge and targeted microorganisms for nitrogen and phosphorus removal, which had reference for the treatment of pollutants in high salt wastewater.

Objective Grouting reinforcement is a common measure to reduce disturbance on existing buildings during tunnel construction. It is essential to focus on the design of GRM (grouting reinforcement mass) parameters in the engineering. Appropriate GRM parameters are crucial to ensure reinforcement effectiveness and reduce project costs. Therefore, it is necessary to optimize and analyze these parameters based on practical engineering conditions. Method Taking the tunneling project of Wuyi Overpass Station to Xinxiu Park Station interval on Nanning Rail Transit Line 5 as example, the under-passing construction is classified by the position relation between existing buildings and tunnel. Numerical calculations are used to optimize the GRM cross-sectional parameters, and the stress mechanism of the GRM is analyzed. On-site grouting reinforcement is carried out according to the parameter optimization results to validate the effectiveness of GRM parameter optimization. Result & Conclusion Under-passing construction is divided into three categories: under-passing directly beneath buildings, side-passing Type I buildings, and side-passing Type II buildings. For the first one, the GRM should extend into the micro-disturbance area by approximately 1 m, with a grouting thickness of 6 m. For the second and third, the GRM should extend approximately 4 m beyond the close tunnel side and penetrate 4 m into the micro-disturbance area on the far tunnel side, with a thickness of 6 m. The stress mechanism of the GRM can be simplified to anchor beams at both ends when under-passing directly beneath buildings and to cantilever beams when side-passing buildings. Monitoring results demonstrate that optimizing the GRM parameters can effectively control building deformation.