Surface-plasmon-polariton (SPP) launchers, which can couple the free space light to the SPPs on the metal surface, are among the key elements for the plasmonic devices and nano-photonic systems. Downscaling the SPP launchers below the diffraction limit and directly delivering the SPPs to the desired subwavelength plasmonic waveguides are of importance for high-integration plasmonic circuits. By designing a submicron double-slit structure with different slit widths, an ultra-broadband (>330 nm) unidirectional SPP launcher is realized theoretically and experimentally based on the different phase delays of SPPs propagating along the metal surface and the near-field interfering effect. More importantly, the broadband and unidirectional properties of the SPP launcher are still maintained when the slit length is reduced to a subwavelength scale. This can make the launcher occupy only a very small area of
While water diversion and dilution are often proposed and implemented for lake eutrophication management, their effectiveness and efficiency in achieving water quality goals is often questionable. Although water quality modeling (WQM) has been applied to quantify lake responses to water diversion and dilution in practice, it is necessary to improve the existing analysis approaches with an uncertainty-based decision-support framework to address the situation of severe data limitation that exists in many realworld cases. This study implemented an enhanced multiple-pattern inverse water quality modeling (MPIWQM) approach in a water diversion study for a terminal plateau lake in southwestern China to address the difficulty of developing robust water-diversion decision support under data limitation and model uncertainty. A two-dimensional, longitudinal and vertical hydrodynamic and water quality model was developed to simulate water circulation and nutrient fate and transport in the lake. To overcome a severe limitation of data, this study employed a multiple-pattern load-parameter estimation (MPLE) method that couples the numerical model with a Genetic Algorithm (GA) and a cluster algorithm to construct an uncertainty-based decision support system. Execution of the MPLE approach resulted in 27 load-parameter patterns for the case study to represent all possible combinations of loading-parameter patterns conditioned on the available water quality data in the lake. The uncertainty-based decision-support framework was then applied to evaluate three realistic water diversion scenarios proposed by local management authorities, and the system was able to predict a range of possibilities given a specific water diversion condition. The scenario analysis results showed that (a) within the range of uncertainties represented by the 27 load-parameter patterns, the model consistently predict that the water diversions would unlikely cause significant water quality improvement in the lake; (b) the water quality response to water diversion demonstrates clear spatial variability, temporal variability, and the effect is in general cumulative over time; (c) different water quality constituents respond to the diversions differently, where the chemical oxygen demand (COD) demonstrates the strongest response, while the total phosphorus (TP) the weakest; and (d) none of the proposed water diversion scenarios is able to reverse, or significantly mitigate the water quality deterioration trend in the lake. (C) 2014 Elsevier B.V. All rights reserved.
By manipulating the surface-plasmon-polariton (SPP) excitation properties of two nanogrooves, we demonstrate unidirectional launching of SPPs using a groove-doublet structure both numerically and experimentally, with the groove separation being downscaled to 1/4 and even 1/8 of the wavelength. Thus, the total lateral dimension of the SPP launcher is only about 1/3 and 1/6 of the wavelength, which is truly subwavelength. The measured extinction ratio at incident wavelength of 800 nm reaches as high as 130 and 18. Such subwavelength SPP unidirectional launchers may have important applications in highly integrated plasmonic circuits. (C) 2014 AIP Publishing LLC.
Understanding of the atmosphere/forest canopy exchange of volatile organic compounds (VOCs) requires insight into the deposition, emission, and chemical reactions of VOCs below the canopy. Between 18 July and 9 August 2009, VOCs were measured with proton-transfer-reaction mass spectrometry (PTR-MS) at six heights between 1 and 6 m beneath a 23 m high mixed-forest canopy. Measured VOCs included methanol, isoprene, acetone, methacrolein and methyl vinyl ketone (MACR + MVK), monoterpenes, and sesquiterpenes. There are pronounced differences in the behaviour of isoprene and its by-products and that of the terpenes. Non-terpene mixing ratios increase with height, suggesting predominantly downward fluxes. In contrast, the terpene mixing ratios decrease with height, suggesting upward fluxes. A 1-D canopy model was used to compare results to measurements with and without surface deposition of isoprene and MACR + MVK and emissions of monoterpenes and sesquiterpenes. Results suggest deposition velocities of 2.7 mm s(-1) for isoprene and 1.2 mm s(-1) for MACR + MVK and daytime surface emission rates of 63 mu g m(-2) h(-1) for monoterpenes. The modelled isoprene surface deposition is approximately 2% of the canopy-top isoprene emissions and the modelled emissions of monoterpenes comprise approximately 15 to 27% of the canopy-top monoterpene emissions to the atmosphere. These results suggest that surface monoterpene emissions are significant for forest canopy/atmosphere exchange for this mixed-forest location and surface uptake is relatively small for all the species measured in this study.
Perceptual learning, a process in which training improves visual discrimination, is often specific to the trained retinal location, and this location specificity is frequently regarded as an indication of neural plasticity in the retinotopic visual cortex. However, our previous studies have shown that "double training" enables location-specific perceptual learning, such as Vernier learning, to completely transfer to a new location where an irrelevant task is practiced. Here we show that Vernier learning can be actuated by less location-specific orientation or motion-direction learning to transfer to completely untrained retinal locations. This "piggybacking" effect occurs even if both tasks are trained at the same retinal location. However, piggybacking does not occur when the Vernier task is paired with a more location-specific contrast-discrimination task. This previously unknown complexity challenges the current understanding of perceptual learning and its specificity/transfer. Orientation and motion-direction learning, but not contrast and Vernier learning, appears to activate a global process that allows learning transfer to untrained locations. Moreover, when paired with orientation or motion-direction learning, Vernier learning may be "piggybacked" by the activated global process to transfer to other untrained retinal locations. How this task-specific global activation process is achieved is as yet unknown.
