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Background and aims: Vegetation restoration can effectively improve multiple soil functions by altering soil microorganisms and physicochemical properties. However, dynamic variations in soil physicochemical properties, microbial communities, and possible pathways to control soil C and N cycles with vegetation restoration are not fully understood. Methods: Therefore, soil physicochemical properties, enzymatic activities, microbial communities, and key C and N cycling processes were investigated in the vegetation sequence on the Chinese Loess Plateau. Results: The results indicated that vegetation restoration had significant positive effects on soil nutrients, C and N cycling rates, and enzymatic activities. Bacterial richness increased significantly along the chronosequence, while fungal richness decreased, but microbial diversity showed less variation. There were no clear covariant trends between soil properties, microorganisms, and nutrient cycles with vegetation restoration. Bacterial and fungal communities were sculptured by similar soil physicochemical indices, which exert more influence on bacteria than on fungi. C cycles were directly and significantly affected by soil physicochemical properties and bacterial composition/richness, but not by fungal communities. N cycles were directly and significantly affected by soil physicochemical properties and fungal composition/richness/diversity, but not by bacterial communities. Furthermore, enzymatic activities were significantly related to C and N cycles, determined mainly by soil physicochemical properties. Soil physicochemical properties, but not microorganism, were key regulators of C and N cycles. Conclusion: Soil physicochemical properties can regulate C and N cycles directly or indirectly by shaping microorganisms or regulating enzymatic activities. The complicated interplay between soil properties, microorganisms, and their regulation of soil nutrient cycleS prevent a clear-cut synergy between the three factors during vegetation restoration. [ABSTRACT FROM AUTHOR]

Named entity recognition (NER) has always been an important research task in information extraction and knowledge graph construction. Due to the randomness of Chinese user-generated reviews, character substitution and informal expression are very common. Its widespread phenomenon leads to that Chinese car reviews NER is still a major challenge. In this paper, we propose a joint multi-view character embedding model for Chinese NER (JMCE-CNER) of car reviews. Firstly, deeper character features are extracted from pronunciation, radical, and glyph views to generate the multi-view character embedding. Secondly, a car domain dictionary is constructed for providing accurate word-level information. Thirdly, the multi-view character embedding and the word-level embedding are jointly fed into the deep learning model to perform the Chinese car reviews NER. The experimental datasets of Chinese car reviews are obtained by manual annotation, containing four types of entities, namely brand, model, attribute and structure of the car. The experimental results on the Chinese car review datasets demonstrate that our proposed model achieves the optimal performance compared with the other state-of-the-art models. Furthermore, the model substantially reduces the impact of character substitution and informal expression on performing NER tasks. [ABSTRACT FROM AUTHOR]

With the rapid growth of social networks, mining customer opinions based on online reviews is crucial to understand consumer needs. Due to the richness of language expressions, customer opinions are often expressed implicitly. However, previous studies usually focus on mining explicit opinions to understand consumer needs. In this paper, we propose a novel implicit opinion analysis model to perform implicit opinion analysis of Chinese customer reviews at both the feature and review levels. First, we extract an implicit-opinionated review/clause dataset from raw review dataset and introduce the concept of the feature-based implicit opinion pattern (FBIOP). Secondly, we develop a clustering algorithm to construct product feature categories. Based on the constructed feature categories, FBIOPs can be mined from the extracted implicit-opinionated clause dataset. Thirdly, the sentiment intensity and polarity of each FBIOP are calculated by using the Chi squared test and pointwise mutual information. Fourthly, according to the resulting FBIOP polarities, the polarities of implicit opinions can be determined at both the feature and review levels. Car forum reviews written in Chinese are collected and labeled as the experimental dataset. The results show that the proposed model outperforms the traditional support vector machine model and the cutting-edge convolutional neural network model. [ABSTRACT FROM AUTHOR]

The effects of vegetation restoration on matrix structure and erosion resistance of iron tailings were studied at dump sites in Malanzhuang, Qian'an, Hebei province, China. The restoration process involved soil spray sowing restoration model with Rhus typhina, soil and iron tailings admixture spray sowing restoration model with Amorpha fruticosa Linn. and six-hole brick restoration model with Pinus tabulaeformis Carrière.–Amorpha fruticosa Linn. mixed-forest, and direct restoration model with Hippophae rhamnoides and Sabina vulgaris. Results show that the composition and distribution of particles and aggregates were closely related to erosion resistance (P < 0.05), indicating that matrix structure of iron tailings play an important role in erosion resistance. The improvement in matrix structure of iron tailings by the different restoration models was in the order of R. typhina soil spray sowing > A. fruticosa soil and iron tailings admixture spray sowing > mixed-forest six-hole brick > H. rhamnoides direct restoration > S. vulgaris direct restoration. The R. typhina soil spray sowing restoration model resulted in the greatest improvement in matrix structure of iron tailings, increasing the clay (10.6%) and large particle aggregates (18.7%) contents significantly (P < 0.01). Simultaneously, particle population, grading conditions (Cu = 28.86, Cs = 1.65), and aggregate stability (6.02) were significantly improved. The A. fruticosa soil and iron tailings admixture spray sowing restoration model, which effectively improved particle distribution (Cu = 8.51, Cs = 1.07), increased the number of large aggregates considerably (9.6%), thereby increasing aggregate stability (6.2). The six-hole brick model significantly increased the number of large aggregates (4.0%) and improved the stability of aggregates (6.2). H. rhamnoides direct restoration improved the stability of aggregates (5.1) but showed no other significant improvements. The effect of S. vulgaris direct restoration on matrix structure of iron tailings was not significant. Due to its dependence on matrix structure of iron tailings, the erosion resistance of R. typhina soil spray sowing restoration model was the greatest, while that of S. vulgaris direct restoration was the weakest. There was no significant difference in the erosion resistance of the other models. Overall, vegetation restoration supplemented by soil spray sowing restoration and engineering measures is superior to in situ direct vegetation restoration in the short-term. In-situ direct restoration has long-term ecological significance because of its advanced concept of near-natural restoration and the advantages of low cost, easy operation, and low secondary damage. [ABSTRACT FROM AUTHOR]

An increasing number of people use social media to share their consumption experiences. Publicly available online reviews have become a significant source of information, which manufacturers use to better understand customer needs and preferences. To facilitate product improvement, this study first considers the inconsistencies between the numerical product ratings and the textual product reviews to establish the inconsistent ordered choice model (IOCM) for measuring customer preferences with regard to product features. The IOCM model effectively reduces the negative impact of inconsistent reviews on the quality of the customer preference measurement model. On the basis of customer preferences obtained from the IOCM model, we then develop a sentiment-based importance–performance analysis (SIPA) model to analyze the categorization of product features for guiding product development. Compared with the original IPA model, the proposed SIPA model in this paper introduces sentiment-importance into the IPA model that makes the product improvement more adaptive to customer preferences. Finally, we empirically evaluate the effectiveness of our proposed IOCM model and illustrate the utility of our proposed SIPA model. [ABSTRACT FROM AUTHOR]

Charge welds occur in profiles during billet-to-billet extrusion of hollow aluminum profiles. To investigate the effects of charge welds on the tensile property of the profile, a tensile test and a fracture scanning test using the scanning electron microscope (SEM) are conducted. The results showed that charge weld plays bad roles in the tensile property of the profile. The tensile samples derived from the charge weld distribution zone are always fractured near the charge welds. In addition, the tensile strengths of the early-stage charge welds are the poorest. To validate the property variations in the charge weld zone along the extrusion directions in a microscale, the evolution of microstructure characteristics and texture in the charge weld distribution zone are discussed with the help of the electron back scattering diffraction (EBSD). The grain morphologies, misorientation, and micro-textures are not uniform along the charge weld in the extrusion direction or on different sides of itself. Incomplete dynamic recrystallization with lower distortion energy and dislocation density due to lack of frictions with dies at the beginning and middle stages of the charge weld results in strip-shaped coarse grains and lower-angle grain boundaries, further revealing the essence of the low tensile strength at the beginning and in the middle of the charge weld. The intensity of shear texture {111}<112> on the charge weld is the largest compared with those on both sides of it, verifying the large plane strain status on the charge weld plane. [ABSTRACT FROM AUTHOR]

The conventional fault analysis method based on symmetrical components supposes that the three-phase parameters of un-transposed transmission line are symmetrical in case of fault. The errors caused by the method with the symmetrical distributed parameter circuit model as the equivalent circuit of the un-transposed ultra high voltage(UHV) transmission line were studied under both normal operation and fault, and the corresponding problems arising were pointed out. By contrast with electromagnetic transient and power electronics(EMTPE) simulation results with the asymmetrical distributed parameter circuit model of un-transposed line, it is shown that the conventional method cannot show the existence of negative and zero sequences before fault happening and there are many errors on voltage and current after fault happening which are different with fault types. The error ranges of voltage and current are 2.13%–81.13% and −7.82%– −86.15%, respectively. [ABSTRACT FROM AUTHOR]