Modelling Fertilizer Use in Relation to Farmers’ Household Characteristics in Three Gorges Reservoir Area, China

Non-point source pollution from excessive use of fertilizers in agriculture is a major cause of the eutrophication problem in China. Understanding farmers’ decision-making concerning fertilization and identifying the influencing factors in this process are key to tackling overfertilization and related pollution issues. This paper reports a study on modelling decisions about fertilizer use based on data collected from 200 farmer households in the Three Gorges Reservoir area of China, using a well-fitted artificial neural network (ANN) with incorporated variance-based sensitivity analysis. The rate of fertilizer use estimated from the model is in good agreement with observed data. The model is further validated and tested by comparing the simulated and observed values. Results show that the model is able to identify the influencing factors and their interactions causing the variation in fertilizer use and to help pinpoint the underlying reasons. It is found that the farmers’ fertilization behavior is greatly affected by the area of cultivated land, followed by the interaction among farmers’ education level, annual income, and awareness of the importance of environmental protection. Future land consolidation is one of several ways to achieve more sustainable fertilization strategies

Growth of millimeter-sized high-quality CuFeSe2_2 single crystals by the molten salt method and study of their semiconducting behavior

An eutectic AlCl$_3$/KCl molten salt method in a horizontal configuration was employed to grow millimeter-sized and composition homogeneous CuFeSe$_2$ single crystals due to the continuous growth process in a temperature gradient induced solution convection. The typical as-grown CuFeSe$_2$ single crystals in cubic forms are nearly 1.6$\times$1.2$\times$1.0 mm3 in size. The chemical composition and homogeneity of the crystals was examined by both inductively coupled plasma atomic emission spectroscopy and energy dispersive spectrometer with Cu:Fe:Se = 0.96:1.00:1.99 consistent with the stoichiometric composition of CuFeSe$_2$. The magnetic measurements suggest a ferrimagnetic or weak ferromagnetic transition below T$_C$ = 146 K and the resistivity reveals a semiconducting behavior and an abrupt increase below T$_C$

Effect of Trace Boron on Microstructure and Mechanical Properties of Ti-9V-3Al-3Cr-3Zr-35Mo Alloy

Conference Name:2nd International Conference on Manufacturing Science and Engineering. Conference Address: Guilin, PEOPLES R CHINA. Time:APR 09-11, 2011.The effects of trace boron on microstructure and mechanical properties of beta type Ti-9V-3Al-3Cr-3Zr-3.5Mo (wt. %) alloy have been investigated in this study. Upon the addition of 0.02 wt. % boron, the grain size of the B-modified alloy was almost four times smaller than that of the B-free alloy. Accordingly, the tensile strength and elongation of B-modified alloy increased from 712 MPa and 14.6 % to 813 MPa and 17.9 %, respectively, mainly due to the effect of grain refinement

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

Heusler type CoNiGa alloys with high martensitic transformation temperature

A strong need exists to develop new kinds of high-temperature shape-memory alloys. In this study, two series of CoNiGa alloys with different compositions have been studied to investigate their potentials as high-temperature shape-memory alloys, with regard to their microstructure, crystal structure, and martensitic transformation behavior. Optical observations and X-ray diffractions confirmed that single martensite phase was present for low cobalt samples, and dual phases containing martensite and gamma phase were present for high cobalt samples. It was also found that CoNiGa alloys in this study exhibit austenitic transformation temperatures higher than 340 degrees C, showing their great potentials for developing as high-temperature shape-memory alloys

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

Guaranteed Lower Bounds for Eigenvalues of Elliptic Operators

In this paper, we provide a method to produce guaranteed lower bounds for eigenvalues of 2m-th order elliptic operators in n dimensions for , especially for elliptic operators with variable coefficients. This method is based on the corresponding Morley-Wang-Xu elements in literature and a unified way to estimate the explicit constants related to the error estimates for the interpolation of Morley-Wang-Xu elements.National Natural Science Foundation of China [11271035, 91430213, 11421101]SCI(E)[email protected]; [email protected]; [email protected]