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Radio frequency interference (RFI) has become a growing concern for weather radar, distorting radar variable estimation. By simultaneously or alternately transmitting the horizontal and vertical polarized waves, polarimetric weather radar can be referred to as SHV radar or AHV radar. The SHV radar can mimic the AHV radar by discarding either H- or V-channel measurements, which leads to an alternating scheme. In this research, the real RFI measurements from an operational C-band SHV radar are used to characterize the RFI temporal, spectral, and polarimetric features. Then, the RFI is simulated to quantify the performance of the object-orientated spectral polarimetric (OBSPol) filter in RFI mitigation. The OBSPol filter has been previously proposed by the authors to mitigate the narrowband clutter (both stationary and moving) and noise. This work extends the application of the filter to remove the RFI for SHV radar. Specifically, by taking advantage of the low copolar correlation of the RFI signal measured in AHV radar, the RFI mitigation method is designed, and its effectiveness is proven by qualitative and quantitative analyses. In particular, in the case of RFI overlapped to weather echoes in the time domain, the RFI can be mitigated, also when the duty cycle of the RFI is high. However, this work does not provide a full evaluation of the RFI mitigation performance on all radar data outputs but a proof of concept to show the effectiveness of the proposed filter for RFI mitigation.

Modular converters such as the multilevel cascaded H-bridge (CHB) are an attractive option for multiple applications mainly because of inherent modularity and fault-tolerant operation. This article is focused on the CHB converter operating with unbalanced conditions (different dc voltages and/or modulation indexes). Under these circumstances, applying the conventional control and modulation strategies, the output voltage harmonic spectrum is degraded. In this article, a generalized variable-angle phase-shifted pulsewidth modulation (PS-PWM) technique for CHB converters with a large number of power modules $(>\!\!3)$ is presented. The method considers all possible cells’ combinations to form groups and assigns the role of each cell in the group. This cell role defines the identifier of the cell in the variable-angle PS-PWM technique. In the steady state, in each group of cells, the harmonic distortion of the CHB output voltage located at twice the carrier frequency $f_c$ is eliminated, while the distortion at $4f_c$ is also diminished. Experimental results show how the proposed technique achieves superior harmonic performance without introducing any significant disadvantage.

The finite control set-model predictive control (FCS-MPC) has been adopted as an excellent choice for the applications of multilevel converters during the last two decades for its salient performance. However, in the case of modular multilevel converters (MMCs), a high amount of calculation is always involved in the implementation, making the FCS-MPC less suitable especially for an MMC with a high number of submodules. To cope with the issue, this article proposes an MPC technique for the MMC with a very low calculation cost. In each sampling period, the arm voltage references of each phase are determined analytically by solving a constrained quadratic programming problem formulated from the cost function. Both a rigorous and simplified procedure is provided to solve the optimization problem. Then, the four nearest candidates around the arm voltage references are evaluated, leading to a proper selection of arm voltage levels. Several experimental tests on an MMC prototype are carried out to validate the effectiveness of the proposed method. Results show that compared with the conventional FCS-MPC method which evaluates all voltage-level combinations, the proposed scheme presents an apparent advantage in terms of calculation cost while achieving similar performance.

This article proposes a new control method for modular multilevel converter (MMC), which is based on a modification of the conventional nearest level control (NLC) scheme implemented by a model predictive control (MPC) technique. Applying the proposed method, the simplicity of the NLC is maintained while the current control ability in terms of both phase current and circulating current is enhanced by the MPC technique. A proper rounding function is used for each arm of the MMC instead of the conventional nearest integer function. The rounding function is determined by evaluating a cost function within the frame of MPC. To validate the proposed technique, a three-phase MMC prototype is employed. The conventional NLC-based control approach of MMC is also evaluated for comparative purposes. Results show that the proposed method exhibits excellent current-regulating ability. Compared with the conventional control scheme, the overall performance is improved without significantly increasing the computational burden or adding relevant complexity to the control system design.

Wind velocity is of great importance for weather monitoring, aviation hazard alerting, wind energy exploring, etc. Doppler radar is widely used to measure wind under rainy condition by sensing the raindrops entrained by the background wind. However, the Doppler velocity, which is a reflection of the raindrops’ velocity in radial direction, is not coincident with the background wind because of the strong inertia of raindrops. Efforts should be made to distinguish the difference between the raindrops’ velocity and the background wind velocity. In this article, we try to establish a relationship between the background wind velocity and the raindrops’ velocity by introducing a definition of the raindrops’ characteristic size, which is related to the velocity characterized by the strongest Doppler spectral component. It is found that the fusion of differential reflectivity and the depolarization ratio can serve as a good proxy for the estimation of the characteristic size. Simulation results for $S$/$C$/$X$-band radars and radar measurements verify the good performance of the proposed retrieval model for the characteristic size, which lays a solid foundation for the retrieval of the background wind velocity.

Besides transition radiation (TR) and synchrotron radiation (SR), Smith-Purcell radiation (SPR) is a simple method to generate powerful terahertz emission. Yet, as the distance from grating surface to electron trajectory increases, the SPR intensity decays exponentially due to the effective interaction range[1] ${h_{\operatorname{int} }} = \frac{\lambda }{{4\pi }}\beta \gamma $. The radiation efficiency is greatly reduced beyond the effective interaction range especially for large diameter beams. To increase the coupling efficiency, an inclined flat electron beam is used in this paper. Meanwhile, the Fabry-Perot resonator arrays take place of the ordinary grating to achieve higher radiation power. This new method of SPR reduces the requirement of electron beam and enhances the radiation intensity. To verify the theory, an electron gun from SJTU is used in experiment, the results of which agree with theoretical analyses and simulations..

The improvements of electrode techniques in recent years make it possible to record hundreds of neurons simultaneously. Neuropixels probe as a type of high-density linear silicon probe, is widely used in rodents' studies to record brain-wide neural activity. However, in vivo electrophysiological recording in non-human primates (NHPs) faces different challenges than in small animals. The challenges faced by the Neuropixels probe of NHPs' recording are addressed in this paper. With targeted improvements, the probe's structure was enhanced to make it more suitable for the acute recording in NHPs. The reinforced probe's shank shows strong stability during different mechanical insertion testing. Furthermore, the recordings were tested on the macaque using standard acute recording procedures which made it possible to densely record hundreds of neurons of different cortical layers in behaving NHPs.

The use of spectral polarimetric filters in the range-Doppler domain shows great promise for clutter mitigation in weather radar applications. One limitation of these filters is that they cannot deal with situations in which ground clutter and precipitation overlap. In this letter, we propose a new signal recovery technique based on kriging in the spectral domain to recover the precipitation in clutter-contaminated areas. Using synthetic radar data, we test our new method and compare its performance to that of Gaussian model adaptive processing and bilinear interpolation. Our results indicate that kriging is the most accurate and robust technique out of the three.

High cross-polarization isolation (CPI) is crucial to the accurate polarization measurement using polarimetric phased array radar (PPAR). In this article, we propose an adaptive direction-dependent polarization state configuration ( $\text {A}{{\text {D}}^{{2}}}\text {PSC}$ ) method to improve the polarization isolation. Compared with the conventional fixed polarization state of radiated wave whether it is linear, circular, or elliptical polarization state, our $\text {A}{{\text {D}}^{{2}}}\text {PSC}$ approach configures the polarization state on basis of beam steering. To achieve the adaptive configuration of magnitude and phase of the dual-polarization antenna, an improved steepest descent algorithm is put forward. To facilitate the uniform representation for the polarization measurement application of PPAR, the universal expressions of intrinsic and measured backscatter matrices are derived for arbitrary polarization state. The dual-polarization dipole array is used to assess the priority of our proposed method. Compared with the conventional approaches, our approach could obtain higher CPI while being available for a larger scanning range. The configured CPI meets the specific polarization requirement for PPAR.

The model predictive control (MPC) strategy has been extensively investigated for the control of modular multilevel converters (MMCs). To avoid the high amount of calculation for the evaluation of all switching states, the MPC can be used to determine only the arm voltage level while the submodule (SM) gate signals are further determined by capacitor voltage sorting scheme. Among such techniques, there are some methods based on the evaluation of adjacent voltage levels, the effectiveness of which diminishes as the number of SMs of MMC increases. To overcome this drawback, this paper proposes a solution based on SM-grouping technique considering the current-regulating capacity. Several simulation tests are carried out on an MMC-based high power system with 128 SMs per arm, the results of which validate the enhancement of performance (steady-state and dynamic) of the MPC method resulted from the proposed approach.

To explore a new surgical approach for chin augmentation using a prosthesis with 3 intraoral vertical incisions whereby placement of the prosthesis is more convenient and accurate, with fewer postoperative complications. Following the anatomic characteristics of the chin, a bilateral mucosal vertical incision and a median observation incision are made. The V-shaped mark on the upper side of the prosthesis can be seen through the observation incision after it is placed from the lateral incision into the predesigned compartment. The incision can be sutured if there is no bleeding in the operation area. Surgery performed in all 19 patients with mild microgenia with 6 to 12 months of follow-up resulted in satisfactory chin and face shape without any complications. The application of this novel method can correct McCarthy type I microgenia with more accurate positioning, less possibility of bilateral sideways and/or up/down movement, and fewer complications.

The performance of a support vector machine (SVM) depends highly on the selection of the kernel function type and relevant parameters. To choose the kernel parameters properly, methods analyzing the class separability have been widely adopted for their efficiency compared with other methods, such as the popular grid search algorithm. This paper proposes a novel index called the Expected Square Distance Ratio (ESDR), which can serve as a better class separability criterion than the existing ones. Experiments on real-world datasets show that, compared with common kernel parameter selection methods that utilize the between-class separation, the variations in ESDR with respect to the kernel parameter are much more in line with those of the classification accuracy, leading to better kernel parameters. Moreover, ESDR takes the exact data distribution into account and can thus be used to study the model selection problem of an SVM for certain forms of data distribution. As an example, we employ the ESDR to analyze the selection of RBF (Radial Basis Function) kernel parameters for Gaussian data classification.

The modular multilevel converters (MMCs) have been extensively adopted in the medium/high power applications in recent years. The main advantages are the modularity and the scalability. However, the unique structure also leads to high cost as well as some control challenges, such as the capacitor energy fluctuation. This paper presents a comparative study of the MMCs based on different submodule (SM) topologies, namely the half-bridge (HB) and the full-bridge (FB). Theoretically analysis of the capacitor energy fluctuation reveals that by employing the FBSMs, the volume of the MMC can be reduced while the performance is enhanced, compared with the MMC based on the HBSMs. A per-SM energy fluctuation index is derived as guideline for the design of FB-MMC. Through the simulations, the proposed design is verified with effectiveness.