ALBERT

Description: Microfibril cellulose (MFC), which is detrimental to soil cultivation and environmental protection, is derived from waste pineapple leaves. Hexagonal boron nitride (h-BN) was modified with polydopamine (PDA)—PDA@h-BN named pBN, and then combined with MFC to prepare a novel hybrid powder. The effect of PDA on h-BN and the binding effect between pBN and MFC were characterized by X-ray photoelectron spectroscopy (XPS), Thermogravimetric (TG), scanning electron microscopy (SEM), and Fourier Transform-Infrared (FT-IR). Poly (vinyl alcohol) (PVA) was used as an eco-friendly polymeric matrix to prepare a pBN-MFC-PVA composite film. The mechanical strength, hydrophobicity, and thermal conductivity of the film were studied and the results confirmed that h-BN was chemically modified with PDA and was uniformly distributed along the MFC. The thermal conductivity of the pBN-MFC-PVA composite film increased with the addition of a pBN-MFC novel powder. MFC acted as “guides” to mitigate the h-BN agglomerate. In addition to the possible usage in the pBN-MFC-PVA composite film itself, the pBN-MFC hybrid powder may be a potential filler candidate for manufacturing thermal interface materials and wearable devices or protective materials.

Description: As one of the most striking topics in the contemporary world economy, the discussion on globalization seems to take capitalism as the main dynamic mechanism for its practice process, i.e., capital-driven globalization. Although many researchers have proposed other alternative solutions that are crucial to the development of globalization, relevant research is still very insufficient. Based on this point, this study aims to explore the driving forces, action mechanisms, manifestations, and influences of the contemporary globalization process in a more comprehensive way, particularly focusing on the dynamic mechanisms of globalization other than capitalism, and trying to explain the interaction between various dynamic mechanisms. Overall, this paper summarizes three major (but not all) dynamic mechanisms of the contemporary globalization: capital-driven, state-driven, and inter-state cooperation-driven. These three dynamic mechanisms act on different spaces in different ways, exert different influences, and have profound interactive relations on the process of globalization. By showing a more comprehensive picture of globalization, this study attempts to explain the existing alternatives to capital-driven globalization, and encourages a more in-depth discussion of anti-globalization and regional integration as alternative options for globalization from the perspective of internal operation mechanism.

Description: Despite the fact that the Bayesian network has great advantages in logical reasoning and calculation compared with the other traditional risk analysis methods, there are still obvious shortcomings in the study of dynamic risk. The risk factors of the earth-rock dam breach are complex, which vary with time during the operation period. Static risk analysis, limited to a specific period of time, cannot meet the needs of comprehensive assessment and early warning. By introducing time factors, a dynamic Bayesian network model was established to study the dynamic characteristics of dam-breach probability. Combined with the calculation of the conditional probability of nodes based on the Leaky Noisy-Or gate extended model, the reasoning results of Bayesian networks were modified by updating the data of different time nodes. Taking an earth-rock dam as an example, the results show that it has less possibility to breach and keep stable along the time axis. Moreover, the factors with vulnerability and instability were found effective, which could provide guidance for dam risk management.

Description: Debris flows have been always a serious problem in the mountain areas. Research on the assessment of debris flows susceptibility (DFS) is useful for preventing and mitigating debris flow risks. The main purpose of this work is to study the DFS in the Shigatse area of Tibet, by using machine learning methods, after assessing the main triggering factors of debris flows. Remote sensing and geographic information system (GIS) are used to obtain datasets of topography, vegetation, human activities and soil factors for local debris flows. The problem of debris flow susceptibility level imbalances in datasets is addressed by the Borderline-SMOTE method. Five machine learning methods, i.e., back propagation neural network (BPNN), one-dimensional convolutional neural network (1D-CNN), decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost) have been used to analyze and fit the relationship between debris flow triggering factors and occurrence, and to evaluate the weight of each triggering factor. The ANOVA and Tukey HSD tests have revealed that the XGBoost model exhibited the best mean accuracy (0.924) on ten-fold cross-validation and the performance was significantly better than that of the BPNN (0.871), DT (0.816), and RF (0.901). However, the performance of the XGBoost did not significantly differ from that of the 1D-CNN (0.914). This is also the first comparison experiment between XGBoost and 1D-CNN methods in the DFS study. The DFS maps have been verified by five evaluation methods: Precision, Recall, F1 score, Accuracy and area under the curve (AUC). Experiments show that the XGBoost has the best score, and the factors that have a greater impact on debris flows are aspect, annual average rainfall, profile curvature, and elevation.

Description: Soil nutrients are the basis of ecological remediation. Soil amendments can form a reticular membrane structure on the soil surface to increase nutrient storage and alleviate nutrient imbalances, and are affected by the environmental temperature. At present, the qualitative evaluation of the effect of soil amendment is mainly based on vegetative growth. However, with the increasing use of soil amendments, how to conveniently and quantitatively evaluate the impact of soil amendments on ecological restoration under different temperature conditions from the perspective of soil urgently needs to be solved. Therefore, a new soil amendment named aqua-dispersing nano-binder (ADNB) and silty clay that is commonly used for ecological restoration in South China were used as research subjects, and the important soil nutrient storage capacity—soil conductivity index—was used as the starting point to find solutions to the above problems. We independently developed a multifunctional instrument to measure the soil amendment concentration. Clay conductivity measurements were used by adding different concentrations of ADNB within the range of 0 to 50 °C, and the mechanism by which temperature and ADNB affect the conductivity of clay was revealed. In addition, the quantitative relationship between the clay conductivity, ambient temperature and concentration of ADNB was elucidated. According to the growth conditions of melinis minutiflora and pigeon pea under different concentrations of ADNB, the optimal ADNB concentration needed to improve ecological restoration was obtained, which provided a new way to evaluate the effects of the large-scale use of soil modifiers on ecological restoration.