Tunable rose petal effect of cobalt coated zinc surfaces via a facile electroless galvanic deposition process

<p>The rose petal effect (large apparent contact angles accompanied by high affinity to water) has greatly inspired researchers recently. In this paper, the rose-petal surfaces with tunable high water adhesion have been prepared successfully via a facile electroless galvanic deposition process as well as the subsequent modification with stearic acid on zinc substrates. We have regulated the concentration of CoSO₄ solution in the process of electroless galvanic deposition to control the surface topography. After being modified with stearic acid, the as-prepared cobalt coated films showed similar apparent contact angles larger than 150° but contrast high water adhesion. To the best of our knowledge, the fabrication of rose petal surfaces with tunable water adhesion is still scarce. The largest water droplet volumes suspended on the tunable rose petal surfaces were 8, 24 and 28 μL, respectively. In addition, based on the different water adhesion on the rose petal surfaces, the selective transportation of microdroplets with different volumes has been demonstrated. We believe that these tunable adhesive rose petal surfaces would have great potential in the droplet-based microreactors.</p

Association between XRCC1 Arg399Gln and risk of head and neck cancer under four genetic models.

<p>Forest plots for a: Gln vs. Arg; b: GlnGln vs. ArgArg; c: ArgGln vs. ArgArg; d: GlnGln+ ArgGln vs. ArgArg. Random-effects models were used for c and d; fixed-effects models were used for a and b. Squares and horizontal lines represent the study-specific OR and 95% CI respectively; diamond indicates the summary OR and 95% CI.</p

Flowchart of the process used for selection of eligible studies.

<p>Flowchart of the process used for selection of eligible studies.</p

Characteristics of the Studies about the XRCC1 Arg399Gln polymorphism (rs25478) Included in the Meta-analysis.

a<p>PB: Population based;</p>b<p>HB: Hospital based;</p>c<p>UK: Unknown or unstated;</p>d<p>HWE: Hardy-Weinberg equilibrium in controls;</p>e<p>MAF: Minor allele frequency in controls.</p

Characteristics of the Studies about the XRCC1 Arg280His polymorphism (rs25489) Included in the Meta-analysis.

a<p>HB: Hospital based;</p>b<p>PB: Population based;</p>c<p>HWE: Hardy-Weinberg equilibrium in controls;</p>d<p>MAF: Minor allele frequency in controls.</p

Stratified analyses of the association of the XRCC1 Arg194Trp (rs1799782), XRCC1 Arg399Gln (rs25487), and XRCC1 Arg280His (rs25489) polymorphisms with HNC risk.

a<p>Number of comparisons;</p>b<p>P-value for Q-test;</p>c<p>The random-effects model was used when the P-value for the Q-test for heterogeneity was <0.05, otherwise the fixed-effects model was used.</p>*<p>Statistically significant, P<0.05.</p

Association between XRCC1 Arg194Trp and risk of head and neck cancer under four genetic models.

<p>Forest plots for a: Trp vs. Arg; b: TrpTrp vs. ArgArg; c: ArgTrp vs. ArgArg; d: TrpTrp+ ArgTrp vs. ArgArg. Random-effects models were used for a, c, and d; a fixed-effects model was used for b. Squares and horizontal lines represent the study-specific OR and 95% CI respectively; diamond indicates the summary OR and 95% CI.</p

Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China

<div><p>Background</p><p>Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS.</p><p>Methods</p><p>Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model.</p><p>Results</p><p>The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve.</p><p>Conclusion</p><p>Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS.</p></div

The selection of the optimal spread of the ARIMA-GRNN hybrid model.

<p>When the spread was 0.006, the RMSE for the testing samples is the least.</p

Parameter estimates and their testing resulting of the final seasonal ARIMA (0,1,1)×(0,1,1)₁₂ model.

<p>Parameter estimates and their testing resulting of the final seasonal ARIMA (0,1,1)×(0,1,1)₁₂ model.</p