The roles of environmental variation and spatial distance in explaining diversity and biogeography of soil denitrifying communities in remote Tibetan wetlands

The relative importance of local environments and dispersal limitation in shaping denitrifier community structure remains elusive. Here, we collected soils from 36 riverine, lacustrine and palustrine wetland sites on the remote Tibetan Plateau and characterized the soil denitrifier communities using high-throughput amplicon sequencing of the nirS and nirK genes. Results showed that the richness of nirS-type denitrifiers in riverine wetlands was significantly higher than that in lacustrine wetlands but not significantly different from that in palustrine wetlands. There was no clear distinction in nir community composition among the three kinds of wetlands. Irrespective of wetland type, the soil denitrification rate was positively related to the abundance, but not the α-diversity, of denitrifying communities. Soil moisture, carbon availability and soil temperature were the main determinants of diversity [operational taxonomic unit (OTU) number] and abundance of thenirS-type denitrifier community, while water total organic carbon, soil NO3- and soil moisture were important in controlling nirK-type denitrifier diversity and abundance. The nirS community composition was influenced by water electrical conductivity, soil temperature and water depth, while the nirK community composition was affected by soil electrical conductivity. Spatial distance explained more variation in the nirS community composition than in the nirK community composition. Our findings highlight the importance of both environmental filtering and spatial distance in explaining diversity and biogeography of soil nir communities in remote and relatively undisturbed wetlands.</p

Real-Time FPGA/CPU-Based Simulation of a Full-Electric Vehicle Integrated with a High-Fidelity Electric Drive Model

Real-time simulations refer to the simulations of a physical system where model equations for one time-step are solved within the same time period as in reality. An FPGA/CPU-based real-time simulation platform is presented in this paper, with a full-electric vehicle model implemented in a central processing unit (CPU) board and an electric drive model implemented in a field programmable gate arrays (FPGA) board. It has been a challenge to interface two models solved with two different processors. In this paper, one open-loop and three closed-loop interfaces are proposed. Real-time simulation results show that the best method is to transmit electric machine speed from the vehicle model to the electric derive model, with feedback electric machine torque calculated in FPGA. In addition, a virtual vehicle testing tool (CarMaker) is used when building the vehicle model, achieving more accurate modeling of vehicle subsystems. The presented platform can be used to verify advanced vehicle control functions during hardware-in-the-loop (HIL) testing. Vehicle anti-slip control is used as an example here. Finally, experiments were performed by connecting the real-time platform with a back-to-back electric machine test bench. Results of torque, rotor speed, and d&amp;q axis currents are all in good agreement between simulations and experiments

Multiplexed Sensor Array for Accurate Time-of-Wetness (TOW) Measurement

In this work, we use electrochemical impedance spectroscopy (EIS) to observe the response of a single, photo-lithographically created, interdigital transducer (IDT) sensor, dimensions 6mm X 6 mm, with capacitive elements 70μm X 500 nm. The IDT was exposed to different wetting conditions, droplets of DI water, 0.1 M NaCl, and 0.6 M NaCl, in volumes of 0.1, 0.3, 1, and 5 μL. Deliquescence of solid NaCl salt particles in a dynamic-humidity (%RH Increasing, 33% to 85%) atmosphere is examined. Equivalent circuit fitting of impedance spectra suggests linear trends for the capacitive equivalent circuit element parameters and a decaying logarithmic trend for the resistive element, with respect to electrolyte concentration vs. area of wetting. The sensor development process includes a 1 by 5 proof-of-concept linear array, and the eventual goal of a 5 by 5 matrix array. The array sensor aims to (1) determine the overall fraction of wet surface area, and (2) distinguish between electrolytes of varying conductivity, in a 2-dimensional gradient across a surface

Highly selective fluorescent chemosensor for Zn2+ derived from inorganic-organic hybrid magnetic core/shell Fe3O4@SiO2 nanoparticles

Magnetic nanoparticles with attractive optical properties have been proposed for applications in such areas as separation and magnetic resonance imaging. In this paper, a simple and novel fluorescent sensor of Zn2+ was designed with 3,5-di-tert-butyl-2-hydroxybenzaldehyde [DTH] covalently grafted onto the surface of magnetic core/shell Fe3O4@SiO2 nanoparticles [NPs] (DTH-Fe3O4@SiO2 NPs) using the silanol hydrolysis approach. The DTH-Fe3O4@SiO2 inorganic-organic hybrid material was characterized by transmission electron microscopy, dynamic light scattering, X-ray power diffraction, diffuse reflectance infrared Fourier transform, UV-visible absorption and emission spectrometry. The compound DTH exhibited fluorescence response towards Zn2+ and Mg2+ ions, but the DTH-Fe3O4@SiO2 NPs only effectively recognized Zn2+ ion by significant fluorescent enhancement in the presence of various ions, which is due to the restriction of the N-C rotation of DTH-Fe3O4@SiO2 NPs and the formation of the rigid plane with conjugation when the DTH-Fe3O4@SiO2 is coordinated with Zn2+. Moreover, this DTH-Fe3O4@SiO2 fluorescent chemosensor also displayed superparamagnetic properties, and thus, it can be recycled by magnetic attraction

Study on the Time-lag Failure of Sandstone With Different Degrees of Unloading Damage

The unloading effect of rock mass excavation is an inevitable practice, and it’s often characterized by a relatively large-scale engineering hazard with a noticeable time lag.A set of unloading triaxial tests were conducted on a sandstone rock to establish the deformation law and the threshold time. Based on the renormalization group theory, the unloading sandstone model was developed by considering the interaction between particles. Similarly, a logistic model was used to predict the unloading damage of sandstone. The unloading time lag damage of sandstone rock was predicted by using the damage threshold. The research shows that: (1) The higher the degree of unloading, the shorter the time-lag failure. (2) The damage range of critical values was optimized. (3) The error between the predicted value and the experimental value of the time threshold was almost less than 5 %, the prediction result was found to be good, and the employed logistic evolution model was reasonable. The findings of this research provide a prediction method and precise information about the mechanism of unloading time lag deformation. Therefore, it can be used as a reference for excavation-support design of underground structures

Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing

The hippocampus has been known as one of the most important structures referred to as Alzheimer’s disease and other neurological disorders. However, segmentation of the hippocampus from MR images is still a challenging task due to its small size, complex shape, low contrast, and discontinuous boundaries. For the accurate and efficient detection of the hippocampus, a new image segmentation method based on adaptive region growing and level set algorithm is proposed. Firstly, adaptive region growing and morphological operations are performed in the target regions and its output is used for the initial contour of level set evolution method. Then, an improved edge-based level set method utilizing global Gaussian distributions with different means and variances is developed to implement the accurate segmentation. Finally, gradient descent method is adopted to get the minimization of the energy equation. As proved by experiment results, the proposed method can ideally extract the contours of the hippocampus that are very close to manual segmentation drawn by specialists

A Review of Dynamic Wireless Power Transfer for In‐Motion Electric Vehicles

Dynamic wireless power transfer system (DWPT) in urban area ensures an uninterrupted power supply for electric vehicles (EVs), extending or even providing an infinite driving range with significantly reduced battery capacity. The underground power supply network also saves more space and hence is important in urban areas. It must be noted that the railways have become an indispensable form of public transportation to reduce pollution and traffic congestion. In recent years, there has been a consistent increase in the number of high‐speed railways in major cities of China, thereby improving accessibility. Wireless power transfer for train is safer and more robust when compared with conductive power transfer through pantograph mounted on the trains. Direct contact is subject to wear and tear; in particular, the average speed of modern trains has been increasing. When the pressure of pantograph is not sufficient, arcs, variations of the current, and even interruption in power supply may occur. This chapter provides a review of the latest research and development of dynamic wireless power transfer for urban EV and electric train (ET). The following key technology issues have been discussed: (1) power rails and pickups, (2) segmentations and power supply schemes, (3) circuit topologies and dynamic impedance matching, (4) control strategies, and (5) electromagnetic interference