Analysis of Frequency Selective Surfaces with Ferrite Substrates

Frequency selective surfaces (FSS) have numerous applications in several microwave and optical systems. Most frequency selective surface structures have one or more dielectric substrates. In this work, instead of traditional dielectric substrates, ferrite substrates are used under different dc bias conditions. By using ferrite materials, one can change the spectral properties of these structures without physically altering them. An applied magnetic field (dc bias) on the ferrite substrate changes its properties and hence the electrical dimensions of the elements comprising the periodic structure. Thus by simply applying a dc bias, the transmission and reflection properties of the periodic structure can be changed. That leads to a tuning mechanism which allows the designer, by varying the externally applied dc magnetic field, to obtain a more desirable frequency response. In this work, the transmission matrices for the ferrite substrate and the air, above and below the ferrite substrate are derived. By combining these transmission matrices along with the boundary conditions, the spectral domain Green\u27s function is obtained. This process is carried out for both the in-plane bias and perpendicular bias of the ferrite. The induced current on the conductor patch is solved by the method of moments in the spectral domain. Roof toping functions are used as both expansion and test functions. Several results are presented to show the tunability of frequency selective surfaces with ferrite substrates as a function of the applied dc bias. Other unique characteristics of the frequency selective surfaces on ferrite substrates are also presented and discussed. The design procedure for frequency selective surfaces by neural network algorithms is introduced

Symmetric implicational restriction method of fuzzy inference

summary:The symmetric implicational method is revealed from a different perspective based upon the restriction theory, which results in a novel fuzzy inference scheme called the symmetric implicational restriction method. Initially, the SIR-principles are put forward, which constitute optimized versions of the triple I restriction inference mechanism. Next, the existential requirements of basic solutions are given. The supremum (or infimum) of its basic solutions is achieved from some properties of fuzzy implications. The conditions are obtained for the supremum to become the maximum (or the infimum to be the minimum). Lastly, four concrete examples are provided, and it is shown that the new method is better than the triple I restriction method, because the former is able to let the inference more compact, and lead to more and superior particular inference schemes

Association of Heart Rate Variability in Taxi Drivers with Marked Changes in Particulate Air Pollution in Beijing in 2008

BACKGROUND: Heart rate variability (HRV), a marker of cardiac autonomic function, has been associated with particulate matter (PM) air pollution, especially in older patients and those with cardiovascular diseases. However, the effect of PM exposure on cardiac autonomic function in young, healthy adults has received less attention. OBJECTIVES: We evaluated the relationship between exposure to traffic-related PM with an aerodynamic diameters <= 2.5 mu m (PM(2.5)) and HRV in a highly exposed panel of taxi drivers. METHODS: Continuous measurements of personal exposure to PM(2.5) and ambulatory electrocardiogram monitoring were conducted on I I young healthy taxi drivers for a 12-hr work shift during their work time (0900-2100 hr) before, during, and after the Beijing 2008 Olympic Games. Mixed-effects regression models were used to estimate associations between PM(2.5) exposure and percent changes in 5-min HRV indices after combining data from the three time periods and controlling for potentially confounding variables. RESULTS: Personal exposures of taxi drivers to PM(2.5) changed markedly across the three time periods. The standard deviation of normal-to-normal (SDNN) intervals decreased by 2.2% [95% confidence interval (0), -3.8% to -0.6%] with an interquartile range (IQR; 69.5 mu g/m(3)) increase in the 30-min PM(2.5) moving average, whereas the low-frequency and high-frequency powers decreased by 4.2% (95% CI, -9.0% to 0.8%) and 6.2% (95% CI, -10.7% to -1.5%), respectively, in association with an IQR increase in the 2-hr PM(2.5) moving average. CONCLUSIONS: Marked changes in traffic-related PM(2.5) exposure were associated with altered cardiac autonomic function in young healthy adults.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000273292800029&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Environmental SciencesPublic, Environmental & Occupational HealthToxicologySCI(E)PubMed65ARTICLE187-9111

Boosting Superior Lithium Storage Performance of Alloy‐Based Anode Materials via Ultraconformal Sb Coating–Derived Favorable Solid‐Electrolyte Interphase

Alloy materials such as Si and Ge are attractive as high‐capacity anodes for rechargeable batteries, but such anodes undergo severe capacity degradation during discharge–charge processes. Compared to the over‐emphasized efforts on the electrode structure design to mitigate the volume changes, understanding and engineering of the solid‐electrolyte interphase (SEI) are significantly lacking. This work demonstrates that modifying the surface of alloy‐based anode materials by building an ultraconformal layer of Sb can significantly enhance their structural and interfacial stability during cycling. Combined experimental and theoretical studies consistently reveal that the ultraconformal Sb layer is dynamically converted to Li3Sb during cycling, which can selectively adsorb and catalytically decompose electrolyte additives to form a robust, thin, and dense LiF‐dominated SEI, and simultaneously restrain the decomposition of electrolyte solvents. Hence, the Sb‐coated porous Ge electrode delivers much higher initial Coulombic efficiency of 85% and higher reversible capacity of 1046 mAh g−1 after 200 cycles at 500 mA g−1, compared to only 72% and 170 mAh g−1 for bare porous Ge. The present finding has indicated that tailoring surface structures of electrode materials is an appealing approach to construct a robust SEI and achieve long‐term cycling stability for alloy‐based anode materials

In Situ Construction of an Ultrarobust and Lithiophilic Li-Enriched Li–N Nanoshield for High-Performance Ge-Based Anode Materials

Alloy-based materials are promising anodes for rechargeable batteries because of their higher theoretical capacities in comparison to graphite. Unfortunately, the huge volume changes during cycling cause serious structural degradation and undesired parasitic reactions with electrolytes, resulting in fragile solid-electrolyte interphase formation and serious capacity decay. This work proposes to mitigate the volume changes and suppress the interfacial reactivity of Ge anodes without sacrificing the interfacial Li+ transport, through in situ construction of an ultrarobust and lithiophilic Li-enriched Li–N nanoshield, which demonstrated improved chemical, electrochemical, mechanical, and environmental stability. Therefore, it can serve as a versatile interlayer to facilitate Li+ transport and effectively block the attack of electrolyte solvents, thus boosting the long-term cycle stability and fast charging capability of Ge anodes. This work offers an alternative methodology to tune the interfaces of other electrode materials as well by screening for more N-containing compounds that can react with Li+ during battery operation

Overview of the MOSAiC expedition: Physical oceanography

Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present alongdrift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean

Where there's smoke there's lung disease

Exposure to biofuels in Chin