8,428 research outputs found

    Land Acquisition, Labor Allocation, and Income Growth of Farm Households

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    This article investigates how land acquisition during urbanization affects labor allocation decisions of farm households in China. We develop an agricultural household model by including land acquisition to examine its impacts on nonfarm labor participation and income. Two data sets (self-designed household surveys at Xingwen County in 2012 and the China Household Finance Survey (CHFS) data covering 29 provinces in 2013) are adopted for empirical analysis. The results find that land reduction has significantly positive effects on the probability and the share of family nonfarm labor allocation from both data sets. We also find that land acquisition increases the household income of the land acquisition group in CHFS data

    STING-mediated disruption of calcium homeostasis chronically activates ER stress and primes T cell death

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    STING gain-of-function mutations cause lung disease and T cell cytopenia through unknown mechanisms. Here, we found that these mutants induce chronic activation of ER stress and unfolded protein response (UPR), leading to T cell death by apoptosis in th

    BIOMECHANICAL EFFECT OF GROUP EXERCISE PROGRAM USING STABILITY BALL ON THE COUNTER MOVEMENT JUMP

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    The purpose of this study was to evaluate the training effect of three-month group exercise program using stability ball. Ten female subjects were recruited to join this group exercise class for three months. The biomechanical parameters of counter-movement jump were collected before and after class. The average of maximal jumping height and the take-off velocity have significantly increased after three months. The group exercise program accoring American College of Sport Medicine trainig guideline which was designed in this study was helpful to increase the jump height of counter movement jump and to improve the biomechanical parameters of the landing

    Coordinated optimal control of secondary cooling and final electromagnetic stirring for continuous casting billets

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    Secondary cooling and final electromagnetic stirring (F-EMS) are both key technologies for continuous casting. These parameters are usually optimized and controlled separately which caused internal quality fluctuations in unsteady conditions. In this paper, a coordinated optimal control strategy based on a multiobjective particle swarm optimization (MOPSO) algorithm is proposed for the parameter optimization of secondary cooling and F-EMS, which is solved based on multiobjective particle swarm optimization (MOPSO) algorithm. The solidification and heat transfer model are developed for the computation of billet temperature and the solidification, and the adaptive grid method is used to improve the diversity and robustness of optimal solutions. The secondary cooling water and F-EMS’ stirring current are dynamically controlled based on the optimization results. The results of field trials showed that the maximum carbon segregation and other quality indexes of billets can be improved significantly

    Controlled Morphological Structure of Ceria Nanoparticles Prepared by Spray Pyrolysis

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    AbstractCeria based materials have been widely used as catalyst supporters and electrolytes. Different applications require different morphologies, and the microstructural control during the synthesis is crucial. In the study, ceria particles were prepared from various precursors using a spray pyrolysis (SP). Comparing to the hollow and porous particles, the formation mechanism with solid spherical structure is not clarified readily. The ceria particles were characterized by transmission electron microscopy, thermogravimetry analysis and X-ray photoelectron spectroscopy. This experimental result suggests that the morphology is controlled by the precursors and could be related to their decomposed behavior during the heating process in SP

    Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

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    Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%

    Density alteration in non-physiological cells

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    In the present study an important phenomenon of cells was discovered: the change of intracellular density in cell's response to drug and environmental factors. For convenience, this phenomenon is named as "density alteration in non-physiological cells" ( DANCE). DANCE was determined by discontinuous sucrose gradient centrifugation (DSGC), in which cells were separated into several bands. The number and position of the bands in DSGC varied with the change of cell culture conditions, drugs, and physical process, indicating that cell's response to these factors was associated with alteration of intracellular density. Our results showed that the bands of cells were molecularly different from each other, such as the expression of some mRNAs. For most cells tested, intracellular density usually decreased when the cells were in bad conditions, in presence of drugs, or undergoing pathological changes. However, unlike other tissue cells, brain cells showed increased intracellular density in 24 hrs after the animal death. In addition, DANCE was found to be related to drug resistance, with higher drug-resistance in cells of lower intracellular density. Further study found that DANCE also occurred in microorganisms including bacteria and fungus, suggesting that DANCE might be a sensitive and general response of cells to drugs and environmental change. The mechanisms for DANCE are not clear. Based on our study the following causes were hypothesized: change of metabolism mode, change of cell membrane function, and pathological change. DANCE could be important in medical and biological sciences. Study of DANCE might be helpful to the understanding of drug resistance, development of new drugs, separation of new subtypes from a cell population, forensic analysis, and importantly, discovery of new physiological or pathological properties of cells
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