Cotton production makes an important contribution to the income of rural residents and the economy in Xinjiang province, which leads other provinces in terms of planted area, total production, and average yield of cotton in China. This study analyzed the competitiveness of cotton production in the study area using the efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI). Moreover, the factors influencing the productivity of cotton have been investigated by the use of ridge regression and correlation matrix using a dataset for the period 2005 to 2018. The results showed that cotton production had a large comparative advantage in Xinjiang from 2005 to 2018. The average of efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI) are 1.50, 12.96, and 4.35, respectively. Overall, Xinjiang cotton production has a higher planting scale advantage and productivity. By using ridge regression to calculate the impact of cotton production on agricultural output value in Xinjiang, the results showed that total cotton production, fiscal expenditure on agricultural support, total agricultural machinery power, and fertilizer use had significant positive effects, whereas cotton sown area, average cotton yield, and the proportion of affected area by insects and diseases had negative impact agricultural output value. The study implies the need for a implementing a well-thought and empirically backed plan to support cotton production based on comparative advantage for a specific area, building a cotton production standard system, reducing the cost of cotton production, and building a cotton risk-protection system to protect the interests of cotton farmers and promote the sustainable development of the cotton industry.
Taylor-Couette-Poiseuille (TCP) flow dominates the inner water-cooling circulation of canned motor reactor coolant pumps. Current research on TCP flow focuses on torque behaviors and flow regime transitions through experiments and simulations. However, research on axial flow resistance in a large Reynolds number turbulent state is not sufficient, especially for the various flow patterns. This study is devoted to investigating the influence of annular flow on the axial flow resistance of liquid in the coaxial cylinders of the stator and rotor in canned motor reactor coolant pumps, and predicting the coolant flow distribution between the upper coil cooling loop and lower bearing lubricating loop for safe operation. The axial flow resistance, coupled with the annular rotation, is experimentally investigated at a flow rate with an axial Reynolds number, Re a , from 2.6 × 10 3 to 6.0 × 10 3 and rotational Reynolds number, Re t , from 1.6 × 10 4 to 4.0 × 10 4. It is revealed that the axial flow frictional coefficient varies against the axial flow rate in linear relation sets with logarithmic coordinates, which shift up when the flow has a higher Re t. Further examination of the axial flow resistance, with the Re a extending to 3.5 × 10 5 and Re t up to 1.6 × 10 5 , by simulation shows gentle variation rates in the axial flow frictional coefficients against the Re a. The relation curves with different Re t values converge when the Re a exceeds 3.5 × 10 5. A prediction model for TCP flow consisting of a polygonal approximation with logarithmic coordinates is developed to estimate the axial flow resistance against different axial and rotational Reynolds numbers for the evaluation of heat and mass transfer during transition states and the engineering design of the canned motor chamber structure.
Assessing climate-induced reductions in cotton yields is critical to developing weather insurance for sustainable agricultural development. Climatic factors such as frost, hail, and drought severely constrain the sustainable development of cotton production in Xinjiang. In this study, based on cotton production and meteorological data from 1988 to 2019 in Aksu, Xinjiang, the H-P filtering method, correlation test, and regression analysis were used to develop a weather index model of cotton yield reduction rate and key meteorological factors. The results showed that the trend yield separated by the H-P filtering method was more stable. The correlation analysis between cotton fertility and meteorological factors concluded that there was a strong positive correlation between precipitation and cotton yield, i.e., the more rainfall, the more unfavorable environment for cotton growth and development. The results of the empirical analysis to determine the net premium rate under different disaster registrations based on the logistic probability distribution model showed that the highest probability of meteorological disasters in the Aksu region was 22.36%, the premium rate was 1.79%, and the net premium was 34.01 RMB per mu. It is found that climate change is closely related to the environment, and human production activities are compatible with the carrying capacity of the environment, otherwise, climate change leads to frequent meteorological disasters, which is not conducive to the sustainable development of agricultural production. It is expected that these research results can provide a relevant basis for the implementation of cotton policy weather insurance in Aksu and other regions and promote the sustainable development of cotton production.
The aldimines (I), prepared from aromatic aldehydes and amino acid esters, are coupled with the αβ‐unsaturated carboxylates or nitriles (II) under phase transfer conditions to form the Michael type adducts (III).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.