Seasonal variations in carbon, nitrogen and phosphorus concentrations and C:N:P stoichiometry in different organs of a Larix principis-rupprechtii Mayr. plantation in the Qinling Mountains, China

Understanding how concentrations of elements and their stoichiometry change with plant growth and age is critical for predicting plant community responses to environmental change. Weusedlong-term field experiments to explore how the leaf, stem and root carbon (C), nitrogen (N) and phosphorous (P) concentrations and their stoichiometry changed with growth and stand age in a L.principis-rupprechtii Mayr. plantation from 2012–2015 in the Qinling Mountains, China. Our results showed that the C, N and P concentrations and stoichiometric ratios in different tissues of larch stands were affected by stand age, organ type andsampling month and displayed multiple correlations with increased stand age in different growing seasons. Generally, leaf C and N concentrations were greatest in the fast-growing season, but leaf P concentrations were greatest in the early growing season. However, no clear seasonal tendencies in the stem and root C, N and P concentrations were observed with growth. In contrast to N and P, few differences were found in organ-specific C concentrations. Leaf N:P was greatest in the fast-growing season, while C:N and C:P were greatest in the late-growing season. No clear variations were observed in stem and root C:N, C:P andN:Pthroughout the entire growing season, but leaf N:P was less than 14, suggesting that the growth of larch stands was limited by N in our study region. Compared to global plant element concentrations and stoichiometry, the leaves of larch stands had higher C, P, C:NandC:PbutlowerNandN:P,andtherootshadgreater PandC:NbutlowerN,C:Pand N:P. Our study provides baseline information for describing the changes in nutritional elements with plant growth, which will facilitates plantation forest management and restoration, and makes avaluable contribution to the global data pool on leaf nutrition and stoichiometry

Synergistic Effect Evaluation of Main and Auxiliary Industry of Power Grid Based on the Information Fusion Technology from the Perspective of Sustainable Development of Enterprises

With the development of the diversified economic union, the power grid enterprises’ auxiliary industries are continuing to grow and develop faster. However, in the process of development, power grid enterprises are still faced with the problem of low efficiency of the management of main and auxiliary and resource allocation and utilization. Thus, the synergistic development evaluation for power grid enterprises’ main and auxiliary industries has a strong practical significance. It can help the managers to find the short board of each industry and search for the exploration direction for improvement to promote the sustainable development of the main and auxiliary industries comprehensively. It can also provide the reference for improving the management level of power grid enterprises. Information fusion technology, as a process of information processing for decision making, can make use of multi-source information synergistically to get a more objective and more essential understanding of the same thing or the same goal. It has been applied to many fields in a mature way. Based on the characteristics of each industry, this paper constructs a synergistic effect evaluation index system of the main and auxiliary industries from the aspects of management foundation, resource integration, operational efficiency and effectiveness. The variable precision fuzzy rough set (VPFRS) is introduced to screen the index system, eliminate redundant indexes, retain key indexes and improve the efficiency and accuracy of evaluation effectively. Meanwhile, based on the characteristic of dealing with the imprecise problem of the vague set, this paper establishes the evaluation model based on information fusion technology of the variable precision fuzzy rough set and vague set (VPFRS-Vague). In order to verify the validity of the model, five typical companies belonging to power grid enterprises are selected as examples for analysis to prove the validity and applicability of the evaluation method

Effect of Metakaolin on the Diffusion Properties of Chloride Ions in Cement Mortar under the Coupling Effect of Multiple Factors in Marine Environment

To address the problem of chloride ion transport in cement concrete in marine environment, this study investigates the effect of metakaolin dosage on the chloride ion diffusion resistance of mortar and its mechanism by testing the chloride ion binding capacity and microstructure of mortar under the coupling effect of chlorine salt-sulfate-carbonation multiple factors. The results show that the coupling of sulfate or carbonation reduces chloride ion transport to some extent compared with single chlorine salt attack, while the three-factor coupled environment promotes free chloride ion diffusion. This is because the products of calcium alumina, gypsum, and calcium carbonate grow together and compete with each other to form more large capillaries; thus, accelerating the diffusion of chloride ions in cement mortar. Metakaolin, due to its higher pozzolanic activity, increases the monocarbon aluminate content in the erosion products, promotes F-salt generation, and increases the Al/Si ratio, which strengthens the binding ability of C-S-H gel to chloride ions, so the free chloride ion concentration inside the specimens doped with metakaolin is lower. In particular, the three-factor coupled environment has less 0.05–10 μm capillary pore content and higher F-salt stability in the specimens, which has the strongest effect on chloride ion curing, and the free chloride ion concentration integral in M-SCCl is reduced by nearly 30% compared with MF-SCCl and F-SCCl

Ice Cover Prediction of a Power Grid Transmission Line Based on Two-Stage Data Processing and Adaptive Support Vector Machine Optimized by Genetic Tabu Search

With the increase in energy demand, extreme climates have gained increasing attention. Ice disasters on transmission lines can cause gap discharge and icing flashover electrical failures, which can lead to mechanical failure of the tower, conductor, and insulators, causing significant harm to people’s daily life and work. To address this challenge, an intelligent combinational model is proposed based on improved empirical mode decomposition and support vector machine for short-term forecasting of ice cover thickness. Firstly, in light of the characteristics of ice cover thickness data, fast independent component analysis (FICA) is implemented to smooth the abnormal situation on the curve trend of the original data for prediction. Secondly, ensemble empirical mode decomposition (EEMD) decomposes data after denoising it into different components from high frequency to low frequency, and support vector machine (SVM) is introduced to predict the sequence of different components. Then, some modifications are performed on the standard SVM algorithm to accelerate the convergence speed. Combined with the advantages of genetic algorithm and tabu search, the combination algorithm is introduced to optimize the parameters of support vector machine. To improve the prediction accuracy, the kernel function of the support vector machine is adaptively adopted according to the complexity of different sequences. Finally, prediction results for each component series are added to obtain the overall ice cover thickness. A 220 kV DC transmission line in the Hunan Region is taken as the case study to verify the practicability and effectiveness of the proposed method. Meanwhile, we select SVM optimized by genetic algorithm (GA-SVM) and traditional SVM algorithm for comparison, and use the error function of mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) to compare prediction accuracy. Finally, we find that these improvements facilitate the forecasting efficiency and improve the performance of the model. As a result, the proposed model obtains more ideal solutions and has higher accuracy and stronger generalization than other algorithms

Effect of Metakaolin on the Microstructural and Chloride Ion Transport Properties of Concrete in Ocean Wave Splashing Zones

In order to address the problem of the durability deficiency of concrete in wave splash zones in a harsh marine environment, this paper investigates the effects of coupled carbonation, sulfate, and chloride salts on the strength, capillary water absorption, and ion migration properties of cement concrete incorporated with metakaolin, and characterizes the pore structural changes with the mercury-pressure method and AC impedance technique. The results show that, compared with a single chloride salt environment, the improvement in mortar strength and impermeability with carbonation coupling is almost positively correlated with the calcium content in the specimen, and renders its pore structure more refined and denser. In contrast, the presence of sulfate reduces mortar strength and increases the ion migration coefficient. When the three factors of sulfate, carbonation, and chloride salt were coupled, damage to the strength and pore structure of the specimens was the most significant, but the specimen incorporated with 30% metakaolin had its strength improved compared with the blank group specimen; from the perspective of pore structural parameters and transport coefficient, the microstructure was denser, and the impermeability was significantly improved

Effects of Ambient Humidity on Water Migration and Hydrate Change in Early-Age Hardened Cement Paste

Ultra-low humidity environments will lead to changes in the microstructure of C–S–H, which will reduce the mechanical properties and service life of cement-based concrete. Thus, to further explore the mechanism on the microscale, this paper studied the water migration and the changes in the hydration products in white cement that was cured for 7 days at 20 °C and at different ambient relative humidities (RHs). The migration and transformation of different types of water in cement paste were studied by low-field nuclear magnetic resonance (NMR). At the same time, Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were used to analyze semi-quantitatively the crystal phase in the hydration products. The results showed that in the first 7 days of the curing process, the content of the different types of water and the hydration products in the cement samples were influenced by the ambient RH. The total water content of the samples will decrease with the decrease in the RH; when the RH decreases to 54% or below, the chemically bound water in the samples will increase with the decline in the RH. Additionally, when the ambient RH is lower than 54%, the grossular will gradually transform into hydrogrossular crystals with the decrease in the RH, and the hibschite with less chemically bound water will transform into katoite with more chemically bound water. In future research, the water migration and hydrate changes under different curing ages, drying processes, and coupling effects should be explored

Structure and Tribological Properties of TiSiN Coatings Prepared by Arc Ion Plating

To study the effects of the Si content on the properties of TiSiN coatings.TiSiN coatings were prepared on Ti6Al4Vby arc ion plating.Surface morphology,microstructures,phase compositions and mechanical properties of the TiSiN coatings with different Si content were characterized by SEM,TEM,EDS,XPS,nanoindentation and tribometer. The results show that the increase of the Si content causes a more fine-grained densification microstructure.At the same time,the hardness increases from about 35GPa to 42GPa.The Si element in the TiSiN coatings exist as amorphous Si_3N_4 and the TiN is wrapped by amorphous Si_3N_4in the TiSiN coatings.When the Si content being 8%,the wear rate of the TiSiN coatings is 2.1*10~(-6) mm~3/(N·m),exhibiting the best tribological properties