Grating-like SERS substrate with tunable gaps based on nanorough Ag nanoislands/moth wing scale arrays for quantitative detection of cypermethrin.

Considering the complexity and high-consumption of the existing approaches to fabricate three-dimensional (3D) regular substrate templates, the scales of the moth wings with evenly-distributed nanoarrays were discovered to provide an ideal bioscaffold for metal silver (Ag) to decorate on to fabricate a flexible, highly-ordered, low-cost and large-scale Ag nanoislands/moth wing (Ag/MW) SERS-active substrate. The grating-like substrate with the optimal morphology of rough and hierarchical Ag nanoislands exhibited high enhancement factor (EF, ~4.16 × 105), low detection limit (10-10 M) to 4-aminothiophenol (4-ATP), outstanding signal uniformity (the relative standard deviations were less than 15%) and superior identification performance in the quantitative detection of pesticide cypermethrin. The three-dimensional finite-difference time-domain (3D-FDTD) method simulated the spatial distribution of the electric field intensity in the substrates with different morphologies, showing a potential strong enhancement of Raman signals in sub-10 nm gaps between two adjacent Ag nanoislands of different layers. These prominent SERS properties of novel Ag/MW SERS-active substrates suggest their potential value in rapid on-side biological and chemical sensing. Meanwhile, the highly-ordered nanoarrays of moth wings provide a new idea for the preparation of regular biomimetic nanomaterials.

Rural areas development and pro-environmental behavior in China: implications for rural development and planning.

This research adds to the body of knowledge by examining the asymmetric link between rural development and pro-environmental behavior in rural China. Rural development is assessed via rural income and digital financial inclusion. We use linear and nonlinear autoregressive distributed lag (ARDL) models to assess short- and long-term effects. The linear analysis suggests that a rise in rural income and digital financial inclusion encourages long-term access to clean fuels and technologies (CFT) in rural areas, while they do not have any significant impact in the short run. On the other side, the nonlinear framework illustrates that a positive shock in rural income and digital financial inclusion encourages long-term access to CFT in rural areas. A negative shock in rural income reduces long-term access to CFT in rural areas, and a negative shock in digital financial inclusion does not significantly impact access to CFT. However, in the short run, only the estimates of rural income are significant, while the estimates attached to digital financial inclusion are insignificant, implying that a rise in rural income increases access to CFT and a fall in rural income reduces access to CFT. Thus, government should encourage collaboration between private sector and civil society organizations to promote sustainable rural development and pro-environmental behavior.

Obesity Mass Monitoring in Medical Big Data Based on High-Order Simulated Annealing Neural Network Algorithm.

With the rapid development of information technology, hospital informatization has become the general trend. In this context, disease monitoring based on medical big data has been proposed and has aroused widespread concern. In order to overcome the shortcomings of the BP neural network, such as slow convergence speed and easy to fall into local extremum, simulated annealing algorithm is used to optimize the BP neural network and high-order simulated annealing neural network algorithm is constructed. After screening the potential target indicators using the random forest algorithm, based on medical big data, the experiment uses high-order simulated annealing neural network algorithm to establish the obesity monitoring model to realize obesity monitoring and prevention. The results show that the training times of the SA-BP neural network are 1480 times lower than those of the BP neural network, and the mean square error of the SA-BP neural network is 3.43 times lower than that of the BP neural network. The MAE of the SA-BP neural network is 1.81 times lower than that of the BP neural network, and the average output error of the obesity monitoring model is about 2.35 at each temperature. After training, the average accuracy of the obesity monitoring model was 98.7%. The above results show that the obesity monitoring model based on medical big data can effectively complete the monitoring of obesity and has a certain contribution to the diagnosis, treatment, and early warning of obesity.

Internal Curing Effect and Compressive Strength Calculation of Recycled Clay Brick Aggregate Concrete.

In order to investigate the internal curing effect of recycled brick aggregate (RBA) in recycled aggregate concrete (RAC) and calculate its contribution to the final compressive strength, two RAC groups with different recycled aggregates and 6 replacement ratios (r) under 4 curing ages were tested. Results show that the compressive strengths of RACI and RACII decrease steadily with the increase of r when below 40%, and that there is a significant drop once the r is higher than 60%. The internal curing effect for RAC with a low RBA ratio is mainly reflected during the curing age of 14-21 days, while for RAC with a high RBA ratio, this internal curing effect appears earlier, during 7-14 days, and becomes very obvious after 14 days. In addition, the actual tested compressive strength of RAC replaced by 100% RBA exceeds around 40% of the expected compressive strength at the age of 28 days. When the age of RAC entirely with RBA is 28 days, the compressive strength caused by the internal curing effect accounts for around 28% of the actual tested compressive strength. The most appropriate r of RBA for RAC production is between 40% to 60%. Finally, the equations for calculating the compressive strength of RAC are presented considering the curing ages, the replacement ratios and the internal curing effect of RBA. Further, a unified equation is suggested for convenience in calculation.

Three-Dimensional Hierarchical Reticular Nanostructure of Fulfora candelaria Wing Decorated by Ag Nanoislands as Practical SERS-Active Substrates.

Although surface-enhanced Raman scattering (SERS) technology has been widely explored nowadays in various fields, the fabrication of practical SERS-active substrates with prominent recognition ability for various analyte molecules is still defective. Natural Fulfora candelaria wing (FCW) with three-dimensional (3D) hierarchical reticular nanostructure was selected as a new bioscaffold for rough silver (Ag) nanoislands to be assembled on to prepare a practical SERS substrate (Ag/FCW substrate). By adjusting the sputtering time of metal Ag, the morphology of the substrates could be easily tuned to control the formation and distribution of "hot spots". Three-dimensional finite-difference time-domain (3D-FDTD) simulation indicated that the excellent SERS performance under optimal morphology was ascribed to the local enhanced electric field in rough Ag surface and effective "hot spot" areas. The SERS measurement results show that the optimal Ag/FCW substrates had high SERS performance in terms of Raman signal sensitivity, reproducibility, uniformity and recognition ability for various analyte molecules. Coupled with flexibility of the biological substrates and the cost effectiveness, the sensitive SERS detection of varied analytes based on Ag/FCW substrates offered great potential for practical applications.

Cloning a DNA marker associated to wheat scab resistance.

Wheat head blight caused mainly by Fusarium graminearum, is an important wheat disease, causing yield and quality losses. The breeding of resistant varieties is the key measure to control this disease, but the conventional breeding method is of low efficiency. The marker-assisted selection (MAS) can significantly improve the breeding efficiency. In this study, four RAPD (randomly amplified polymorphic DNA) markers linked to FHB resistance were obtained and one was cloned and sequenced. F7 recombinant inbred lines (RILs) were derived from the F1 of the cross Ning894037 (resistant)/Alondra (susceptible) by the single-seed descent method. Scab resistance of F7 RILs was evaluated in the greenhouse by injecting conidiospores into a central floret. Scab symptoms were evaluated on the 21st day after inoculation. Disease severity was assessed as the percentage of infected spikelets/spike. The F7 RIL population displayed a normal distribution, transgressive segregation and significant variation for FHB severity. DNA from resistant and susceptible parents was analyzed with 520 RAPD primers. Four markers (S1384-640,S1360-600, S1319-350,S1319-820) linked to FHB resistance were obtained. DNA of S1384-640 was recovered, subjected to re-amplification by using S1384 primer and the same protocol as for RAPD analysis and identified the rightness. The PCR product of S1384-640 was ligated into the pUCm-T vector, and cloned into fresh competent cells of Escherichia coli strain DH5alpha RAPD analysis showed that the inserts of the recombinant plasmids were DNA of S1384-640. The sequencing result showed that the cloned fragment was 648 bp.