Radiating twisted beams, Orbital Angular Momentum (OAM) based radar provides a new perspective for present radar techniques. However, estimation methods now used has a demerit of resolution. Thus, we raised Multiple Signal Classification (MUSIC) algorithm to improve resolution ability based on this innovative concept. The echo model based on uniform circular array (UCA) for MUSIC was first built. In contrast to uncorrelated signals in classical MUSIC algorithm, echo signals from targets are fully coherent with each other. Spatial smoothing technique was subsequently utilized in OAM regime to tackle it. Simulation results showed the super-resolution capacity of MUSIC to detect objectives compared to the traditional Fast Fourier Transform (FFT) method. Introduction: Orbital Angular Momentum (OAM) has been widely studied in optic regime regarding imaging, microscopic particle and communication [1,2]. While radio OAM had not been explored until Bo. Thide et al. first proved the effectiveness of OAM generating in a low-frequency band in [3]. The numerous orthogonal helical beams entitle OAM a larger freedom degree, benefiting high capacity of communication and enriching radar targets more information. Recent work on radio OAM consists of two parts, i.e. antennas design to produce twisted beams and OAM multiplexing in communication system. Several approaches including circular array [4-6], spiral phase plate [7-8], higher resonate mode [9] are employed to engender electromagnetic vortex. Meanwhile, OAM multiplexing from simulations to outdoor experiments [10-12] were conducted to attain a high-capacity communication. Radar based on this concept had not attracted much attention until Guo et al. [13] first proposed OAM based target detection model, opening a new perspective for existing radar techniques. Such system generates various twisted beams to illuminate targets as shown in Fig.1 and receive echo signals in a reverse way. By making a Fast Fourier Transform (FFT) or back projection of received signals, this scheme manifests azimuthal resolution ability without relative moves or beams scanning. Additionally, no complex waveform is needed for this scenario. Later, [14] further extended the detection model to Multiple-in-multiple-out (MIMO) and Multiple-in-single-out (MISO) modes. Besides, two-dimension imaging method by exploiting OAM and frequency diversity was studied as well. Both papers utilized traditional methods like FFT and black projection to make estimations of azimuth angle. To gain a high resolution, numerous samples in OAM domain are required, thus increasing complexity of the system. Therefore, super-resolution techniques based on OAM radar detection are in demand. This paper built the model and derived spatial smoothing multiple signal classification (MUSIC) [15] algorithm to gain super-resolution estimations of targets.
Sanjiang National Nature Reserve (NNR) is a state-owned natural wetland in China that has suffered severe degradation due to cultivation and wetland reclamation by farmers. As a consequence, the conversion of cultivated land to wetlands (CCW) was proposed by the government of Heilongjiang province and the United Nations Development Programme/Global Environment Facility (UNDP/GEF) project team in 2007. We suggest that voluntary participation in the CCW could be an important tool for accomplishing the integrated objectives of wetland conservation and local development. The purpose of this study was to examine the main factors that influence farmers' willingness to participate in the CCW through a field investigation and a questionnaire. Based on the data from our questionnaire, which provided an effective sample of 310 households in 11 villages, the influencing factors of farmers' willingness to participate were analyzed through binary logistic regression analyses. It was concluded that age, education, the amount of cultivated land, geographical location, and the perceived benefits and risks were important factors for participation. Furthermore, suggestions for improving the wetland compensation system and providing alternative livelihoods are proposed to strengthen participation.
In this work, the development of subharmonic emission based noninvasive pressure estimation technique is presented. In vitro, ambient pressures were varied (between 0 and 120 mmHg) in a closed-loop flow system circulating 0.2 ml Sonazoid microbubbles (GE Healthcare, Oslo, Norway) suspended in 750 ml of isotonic diluent and recorded by a Millar pressure catheter as the reference standard. Simultaneously, a SonixRP ultrasound scanner (Ultrasonix Medical Corp., Richmond, BC, Canada) operating in pulse inversion mode (f transmit : 2.5 MHz) was used to acquire unprocessed RF data at five different incident acoustic pressures (from 76 kPa to 897 kPa; n=3). The subharmonic data for each pulse was extracted using band-pass filtering with averaging, and subsequently, processed to eliminate noise. The incident acoustic pressure most sensitive to ambient pressure fluctuations was determined; then the ambient pressure was tracked over 20 seconds. Regression analysis compared subharmonic and catheter pressure values. In vivo validation of this technique was performed noninvasively for tracking left ventricular (LV) pressures of two canines using similar post processing as in vitro. The subharmonic signal tracked ambient pressures with r 2 = 0.922 for 20 seconds in vitro. In vivo the subharmonic signal tracked the LV pressures with r 2 > 0.790. Maximum errors in estimating clinically relevant systolic and diastolic pressures ranged from 0.22 to 2.84 mmHg using this subharmonic technique relative to Millar catheter pressures. Clinical validation and real time implementation of this technique may ultimately lead to the first noninvasive cardiac pressure monitoring tool.
This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000-2015. The slacks-based measure (SBM) model, spatial autocorrelation, and the geographically weighted regression (GWR) model were used to conduct the analysis. The conclusions were as follows: first, the overall efficiency of green development of the Xuzhou Metropolitan Area decreased, the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency. Second, the counties with high-efficiency green development were distributed along the coast, and along the routes of the Beijing-Shanghai and the Eastern Longhai railways. A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency. Third, regarding spatial correlation and green development efficiency, the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu, whereas the Low-Low type counties were concentrated in the external, marginal parts of the metropolitan area. Fourth, the major factors (ranked in decreasing order of impact) influencing green development efficiency were innovation, government regulations, the economic development level, energy consumption, and industrial structure. These factors exerted their influence to varying extents; the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.
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