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Silver particles have been widely used in SERS detection as an enhancement substrate. The large-scale synthesis of Ag particles with controllable size and shape is still a challenge. We demonstrate a high-throughput method for the preparation of monodisperse submicron silver particles using S-shaped microfluidic chips. Submicron silver particles were prepared by a simplified reduction method. By adjusting the concentration of the reducing agent ascorbic acid and the stabilizer PVP, the particle size and morphology could be controlled, obtaining a size distribution of 1–1.2 μm for flower-like silver particles and a size distribution of 0.5–0.7 μm for quasi-spherical silver particles. This microfluidic system can be used to fabricate submicron silver particles on a large scale, continuously and stably, with a production efficiency of around 1.73 mg/min. The synthesized submicron silver particles could realize ultra-sensitive SERS detection, and the lowest concentration of rhodamine 6G (R6G) that could be detected was 10−9 M. [ABSTRACT FROM AUTHOR]

The combination of microfluidic technology and surface-enhanced Raman spectroscopy (SERS) has the advantages of being label-free, fingerprint spectroscopy, and high sensitivity, which giving the combination great potential for rapid trace-level biological and environmental analysis. In this review, we summarized the recent progress in these two fields, e.g., microfluidics and SERS, including the basic strategies of a simple and versatile microfluidic-SERS detection system and its wide-ranging applications. Moreover, we listed the main challenges and future directions of the microfluidic-SERS systems; proposed on-chip applications beyond SERS; developed a more efficient, more sensitive, and more convenient microfluidic-SERS system; and formed a more complete on-site real-time detection technology. [ABSTRACT FROM AUTHOR]

The ability to remove noise from remote sensing images, while retaining the important features of the images, is becoming increasingly important. In this paper, we introduce the multi-band contourlet transform, a new method for adaptively denoising remote sensing images. We describe existing methods that use multi-resolution analysis transforms for denoising images and discuss their respective advantages and disadvantages. We then introduce our novel denoising method, which exploits the advantages of existing methods. We summarize the results of a comprehensive set of experiments designed to evaluate the performance of our method and compare it with the performance of existing methods. The results demonstrate that our method is superior to existing methods, both in terms of its ability to denoise images and to retain salient features of those images following denoising. [ABSTRACT FROM AUTHOR]

Leaf respiration is an important component of carbon exchange in terrestrial ecosystems, and estimates of leaf respiration directly affect the accuracy of ecosystem carbon budgets. Leaf respiration is inhibited by light; therefore, gross primary production (GPP) will be overestimated if the reduction in leaf respiration by light is ignored. However, few studies have quantified GPP overestimation with respect to the degree of light inhibition in forest ecosystems. To determine the effect of light inhibition of leaf respiration on GPP estimation, we assessed the variation in leaf respiration of seedlings of the dominant tree species in an old mixed temperate forest with different photosynthetically active radiation levels using the Laisk method. Canopy respiration was estimated by combining the effect of light inhibition on leaf respiration of these species with within-canopy radiation. Leaf respiration decreased exponentially with an increase in light intensity. Canopy respiration and GPP were overestimated by approximately 20.4% and 4.6%, respectively, when leaf respiration reduction in light was ignored compared with the values obtained when light inhibition of leaf respiration was considered. This study indicates that accurate estimates of daytime ecosystem respiration are needed for the accurate evaluation of carbon budgets in temperate forests. In addition, this study provides a valuable approach to accurately estimate GPP by considering leaf respiration reduction in light in other ecosystems. [ABSTRACT FROM AUTHOR]