ALBERT

Description: Due to its adjustable electronic properties and effective excitation of surface plasmons in the infrared and terahertz frequency range, research on graphene has attracted a great deal of attention. Here, we demonstrate that plasmon modes in graphene-coated dielectric nanowire (GNW) waveguides can be excited by a monolayer graphene ribbon. What is more the transverse resonant frequency spectrum of the GNW can be flexibly tuned by adjusting the chemical potential of graphene, and amplitude of the resonance peak varies linearly with the imaginary part of the analyte permittivity. As a consequence, the GNW works as a probe for capturing the molecular spectrum. Broadband sensing of toluene, ethanol and sulfurous anhydride thin layers is demonstrated by calculating the changes in spectral intensity of the propagating mode and the results show that the intensity spectra correspond exactly to the infrared spectra of these molecules. This may open an effective avenue to design sensors for detecting nanometric-size molecules in the terahertz and infrared regimes.

Description: The authors combine the cellular automata with particle system to realize the three-dimensional modeling and visualization of the cloud in the paper. First, we use the principle of particle systems to simulate the outline of the cloud; generate uniform particles in the bounding volumes of the cloud through random function; build the cloud particle system; and initialize the particle number, size, location and related properties. Then the principle of cellular automata system is adopted to deal with uniform particles simulated by the particle system to make it conform to the rules set by the user, and calculate its continuous field density. We render the final cloud particles with a texture map and simulate the more realistic three-dimensional cloud. This method not only obtains the real effect in the simulation, but also improves the rendering performance.

Description: Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.

Description: Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past three decades in the Upper Heihe River Basin (UHRB), a complex multiple use watershed in arid northwestern China. We apply empirical orthogonal function (EOF) and singular value decomposition (SVD) analysis to isolate and identify the spatial patterns of satellite-derived leaf area index (LAI) and their close relationship with the variability of an aridity index (AI = Precipitation/Potential Evapotranspiration). Results show that UHRB has become increasingly warm and wet during the past three decades. In general, the rise of air temperature and precipitation had a positive impact on mean LAI at the annual scale. At the monthly scale, LAI variations had a lagged response to climate. Two major coupled spatial change patterns explained 29% and 41% of the LAI dynamics during 1983–2000 and 2001–2010, respectively. The strongest connections between climate and LAI were found in the southwest part of the basin prior to 2000, but they shifted towards the north central area afterwards, suggesting that the sensitivity of LAI to climate varied over time, and that human disturbances might play an important role in altering LAI patterns. At the basin level, the positive effects of regional climate warming and precipitation increase as well as local ecological restoration efforts overwhelmed the negative effects of overgrazing. The study results offer insights about the coupled effects of climatic variability and grazing on ecosystem structure and functions at a watershed scale. Findings from this study are useful for land managers and policy makers to make better decisions in response to climate change in the study region.

Description: Studying the impact of vegetation dynamics on hydrological processes is essential for environmental management to reduce ecological environment risk and develop sustainable water management strategies under global warming. This case study simulated the responses of streamflow to vegetation cover degradation under climate variations in the Xilin River Basin in a semi-arid steppe of northern China. The snowmelt and river ice melting processes in the Soil and Water Assessment Tool (SWAT) were improved to estimate the changes in streamflow under multiple scenarios. Results showed that the improved SWAT simulations matched well to the measured monthly streamflow for both calibration (determination coefficient R2 = 0.75 and Nash–Sutcliffe ENS = 0.67) and validation periods (R2 = 0.74 and ENS = 0.68). Simulations of vegetation change revealed that obvious changes occurred in streamflow through conversion between high and low vegetation covers. The reductions in vegetation cover can elevate streamflow in both rainfall and snowmelt season, but the effects are most pronounced during the rainfall seasons (i.e., the growing seasons) and in drier years. These findings highlight the importance of vegetation degradation on modifying the hydrological partitioning in a semi-arid steppe basin. We conclude that in a particular climate zone, vegetation cover change is one of the important contributing factors to streamflow variations. Increases in streamflow in water-limited regions will likely reduce the effective water content of soil, which in turn leads to further degradation risk in vegetation. Therefore, vegetation cover management is one of the most effective and sustainable methods of improving water resources in water-constrained regions.

Description: Energies, Vol. 10, Pages 1054: RTV Silicone Rubber Degradation Induced by Temperature Cycling Energies doi: 10.3390/en10071054 Authors: Xishan Wen Xiaoqing Yuan Lei Lan Lu Hao Yu Wang Shaodong Li Hailiang Lu Zhenghong Bao Room temperature vulcanized (RTV) silicone rubber is extensively used in power system due to its hydrophobicity and hydrophobicity transfer ability. Temperature has been proven to markedly affect the performance of silicone rubbers. This research investigated the degradation of RTV silicone rubber under temperature cycling treatment. Hydrophobicity and its transfer ability, hardness, functional groups, microscopic appearance, and thermal stability were analyzed using the static contact angle method, a Shore A durometer, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetry (TG), respectively. Some significant conclusions were drawn. After the temperature was cycled between −25 °C and 70 °C, the hydrophobicity changed modestly, but its transfer ability changed remarkably, which may result from the competition between the formation of more channels for the transfer of low molecular weight (LMW) silicone fluid and the reduction of LMW silicone fluid in the bulk. A hardness analysis and FTIR analysis demonstrated that further cross-linking reactions occurred during the treatment. SEM images showed the changes in roughness of the RTV silicone rubber surfaces. TG analysis also demonstrated the degradation of RTV silicone rubber by presenting evidence that the content of organic materials decreased during the temperature cycling treatment.