BiMGCL: rumor detection via bi-directional multi-level graph contrastive learning.

The rapid development of large language models has significantly reduced the cost of producing rumors, which brings a tremendous challenge to the authenticity of content on social media. Therefore, it has become crucially important to identify and detect rumors. Existing deep learning methods usually require a large amount of labeled data, which leads to poor robustness in dealing with different types of rumor events. In addition, they neglect to fully utilize the structural information of rumors, resulting in a need to improve their identification and detection performance. In this article, we propose a new rumor detection framework based on bi-directional multi-level graph contrastive learning, BiMGCL, which models each rumor propagation structure as bi-directional graphs and performs self-supervised contrastive learning based on node-level and graph-level instances. In particular, BiMGCL models the structure of each rumor event with fine-grained bidirectional graphs that effectively consider the bi-directional structural characteristics of rumor propagation and dispersion. Moreover, BiMGCL designs three types of interpretable bi-directional graph data augmentation strategies and adopts both node-level and graph-level contrastive learning to capture the propagation characteristics of rumor events. Experimental results on real datasets demonstrate that our proposed BiMGCL achieves superior detection performance compared against the state-of-the-art rumor detection methods.

Comparative life cycle assessment of the linear and circular wine industry chains: a case study in Inner Mongolia, China.

Environmental issues and the sustainability of the wine industry receive widespread public attention, but few studies address the environmental impact of the circular wine industry chain. Therefore, we applied the life cycle assessment (LCA) method to a wine enterprise in Inner Mongolia, China, to conduct a cradle-to-gate assessment and comparative analysis on the linear and circular wine industry chain scenarios. The results show that the circular industry chain (S2) has better environmental benefits; the total value of each environmental impact category of S2 is reduced by more than 80% compared with that of the linear industry chain (S1). The global warming potential of S1 is decreased from 4.88 kg CO2eq to 0.919 kg CO2eq for S2. Viticulture is the primary source of environmental problems in all life cycle stages of both scenarios, and electricity and diesel consumption are the key factors affecting the results. Our study shows that the optimization of S2 significantly improves resource efficiency and energy utilization and alleviates the environmental burden through proper waste recycling. Finally, we proposed optimization suggestions based on S2. This study provides scientific guidance for promoting the wine industry to build a circular industry chain and optimize the industrial structure, thus promoting the sustainable development of the industry.

[Heavy Metal Pollution and Health Risk Assessment of Mine Soil in Yangtze River Economic Belt].

The study of heavy metal pollution in mine soil of the Yangtze River Economic Belt is important for promoting the ecological restoration of mines and the construction of green mines in the Yangtze River Economic Belt. For this study, we collected the relevant research on the pollution of heavy metals in the mine soil of the Yangtze River Economic Belt from 2006 to 2020 and studied the pollution status, distribution law, and health risk of heavy metals by using the land accumulation index method, Kriging interpolation method, and health risk assessment method. The results showed that the average contents of Pb, Cd, Cr, Hg, As, Zn, Ni, and Cu in mine soil far exceeded the background value in China, and the accumulation degree of Cd and Hg was significant. The pollution evaluation results showed that the pollution degree of the eight heavy metals was Cd>Hg>Pb>Zn>Cu>As>Ni>Cr, the pollution degree of Cd and Hg was the highest, and more than 60% of the sample points were at medium pollution. The pollution evaluation showed that the soil pollution of tin and lead-zinc mines was more prominent than that of other minerals. The health risk assessment indicated that oral intake was the main intake route for non-carcinogenic and carcinogenic risks, the total non-carcinogenic and carcinogenic risk index was within the unacceptable range, and the non-carcinogenic and carcinogenic risk of mine soil in the middle and upper reaches of the Yangtze River Economic Belt was significantly higher than that in the lower reaches.

The Degradation Properties of MgO Whiskers/PLLA Composite In Vitro.

In this study, composite films of stearic acid⁻modified magnesium oxide whiskers (Sa⁻w-MgO)/poly-l-lactic acid (PLLA) were prepared through solution casting, and the in vitro degradation properties and cytocompatibility of the composites with different whisker contents were investigated. The results showed that the degradation behavior of the composite samples depended significantly on the whisker content, and the degradation rate increased with the addition of MgO content. Furthermore, the degradation of the composites with higher contents of whiskers was influenced more severely by the hydrophilicity and pH value, leading to more final weight loss, but the decomposition rate decreased gradually. Furthermore, the pH value of the phosphate buffer solution (PBS) was obviously regulated by the dissolution of MgO whiskers through neutralization of the acidic product of PLLA degradation. The cytocompatibility of the composites also increased remarkably, as determined from the cell viability results, and was higher than that of PLLA at the chosen whisker content. This was beneficial for the cell affinity of the material, as it notably led to an enhanced biocompatibility of the PLLA, in favor of promoting cell proliferation, which significantly improved its bioactivity, as well.

[Relationship between modular growth characteristics of five plant species and water and heat combination in warm-temperate and moderate-temperate steppes].

Applying comparative study on the characteristics of modular growth of five mutual species such as Stipa grandis, Leymus chinensis, Cleistogenes squorrosa, Lespedeza dahurica and Heteropappus altaicus, the grey-correlative analyses between the demographic growth analysis indexes and average temperature, precipitation and moisture had been carried out during months of the growth seasons from 1999 to 2000 in Research Stations of warm-temperate and moderate-temperate steppes of Inner Mongolia. The results demonstrated that the indexes of DRGR & DRGRa and DULA of these species were all higher in moderate-temperate steppe than warm-temperate steppe, showing the ecological characteristics of adaption themselves to the climate of shorter growth season and inadequate thermal condition, while longer duration of leaf area and modular quantity (DLAD & DMND) of these species reflected the adaption of the longer growth season and sufficient quantity of heat in warm-temperate steppe. Meanwhile, the greycorrelative degree between modular growth indexes of these species and moisture was remarkably higher in warm-temperate steppe than in moderate-temperate steppe, showing that modular growth of plant individual was more sensitive to the combination of water and heat in growth season in warm-temperate steppe, and indicating the response characteristics of plant modular growth in different thermal steppe region.