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Deep learning is applied to assist the joint inversion for audio-magnetotelluric and seismic travel time data. More specifically, deep residual convolutional neural networks (DRCNNs) are designed to learn both structural similarity and resistivity–velocity relationships according to prior knowledge. During the inversion, the unknown resistivity and velocity are updated alternatingly with the Gauss–Newton method, based on the reference model generated by the trained DRCNNs. The workflow of this joint inversion scheme and the design of the DRCNNs are explained in detail. Compared with describing the resistivity–velocity relationship using empirical equations, this method can avoid the necessity in modeling the correlations in rigorous mathematical forms and extract more hidden prior information embedded in the training set, meanwhile preserving the structural similarity between different inverted models. Numerical tests show that the inverted resistivity and velocity have similar profiles, and their relationship can be kept consistent with the prior joint distribution. Furthermore, the convergence is faster, and final data misfits can be lower than separate inversion.

In this communication, a novel dipole configuration with reactive loadings is proposed for the design of low-profile dual-band dual-polarized stacked antenna arrays. For lower band (LB1, 3.3–3.6 GHz) dipole, its inductive loadings are implemented at the end of each dipole arm to suppress the basic resonant mode for band rejection at higher frequencies. For higher band (HB2, 4.8–5.0 GHz) dipole, its LC loadings are implemented at the beginning of each dipole arm, where the inductor and the capacitor, respectively, increase the $Q$ -factor for improving the out-of-band rejection and balance the impedance matching. Hence, LB1 and HB2 dipoles can be closely stacked with high isolation. Moreover, a dual-band artificial magnetic conductor (AMC) reflector is adopted for reducing the distance between the antenna and the ground plane. Consequently, the overall height of the proposed one is only 0.16 $\lambda _{L}$ ( $\lambda _{L}$ being the free-space wavelength at the center frequency of LB1), which is smaller than the previous dual-band stacked designs. The measurement results demonstrate that the array achieves good impedance matching, high isolation, and stable radiation patterns simultaneously, indicating it as a promising candidate for sub-6 GHz base-station services.

This communication presents a novel decoupling device called a cascaded power dividing decoupling network (C-PDDN). It is cascaded with two antennas operating in adjacent or even contiguous frequency bands to reduce the mutual coupling. To achieve high isolations at $n$ desired frequency points, an $n$ -order C-PDDN can be accordingly designed. Each order PDDN consists of two power dividers (PDs), two sections of transmission lines, and one reactive component. Explicit design formulas are presented to calculate the design parameters of the C-PDDN to meet the required isolation criteria. To validate the decoupling concept, a two-order C-PDDN is designed and applied to a testing array that consists of two base-station dipole antennas, one of which serves the time-division long-term evolution (2300–2400 MHz) and the other for wireless fidelity system (2400–2483.5 MHz). The simulated and measured results demonstrate that the proposed two-order C-PDDN could decrease the mutual coupling by over 20 dB, verifying the decoupling methodology.

The emergence of highly directional beamforming technology makes millimeter wave frequency band communication possible in future wireless communication networks. Based on the multipath characteristics of millimeter wave frequency communication, a high-precision multipath channel estimation algorithm based on signal subspace is proposed. In the mobile terminal, an iterative heuristic radio frequency combination algorithm based on spatial points is proposed. The analog precoding at the base station uses deep learning to accelerate the calculation, and then the multi-user communication is modeled to design the digital precoding. The simulation results show that the multi-channel estimation algorithm can estimate 4 paths with an error of no more than 0.3 rad. The proposed DL algorithm takes only 20% of the time when it is close to the 87% spectral efficiency of the traditional algorithm.

In this letter, a hybrid translation computation method for the multilevel fast multipole algorithm (MLFMA) is proposed based on machine learning. The hybrid method combines both generalized regression neural network (GRNN) and artificial neural network (ANN) to replace the traditional translation procedure during the solving process of the MLFMA. Based on the data corresponding to every one of the interaction list boxes at each level, the hybrid neural network is trained. Comparing with the previous machine learning method in this field, the proposed model is more general, and with lower complexity since it inherits the accuracy of the GRNN as well as the efficiency of the ANN. To the best of our knowledge, it is for the first time that the ANN is integrated into the MLFMA. Numerical examples are benchmarked to illustrate the reliability and capability, thus making it possible to solve similar problems during the fast inhomogeneous plane wave algorithm solving process in the multilayered medium.

This letter proposes a novel deep learning (DL) approach to resolve the electromagnetic inverse scattering (EMIS) problems. The conventional approaches of resolving EMIS problems encounter assorted difficulties, such as high contrast, high computational cost, inevitable intrinsic nonlinearity, and strong ill-posedness. To surmount these difficulties, a novel DL approach is proposed based on a novel complex-valued deep fully convolutional neural network structure. The proposed complex-valued deep learning model for solving EMIS problems composes of an encoder network and its corresponding decoder network, followed by a final pixel-wise regression layer. The complex-valued encoder network extracts feature fragments from received scattered field data, while the role of the complex-valued decoder network is mapping the feature fragments to retrieve the final contrasts (permittivities) of dielectric scatterers. Hence, the proposed deep learning model functions as an “heterogeneous” transformation process, where measured scattering field data is converted into the corresponding contrasts of scatterers. As a consequence, the EMIS problem could be resolved accurately even for extremely high-contrast targets. Numerical benchmarks have illustrated the feasibility and accuracy of our proposed approach. The proposed approach opens a novel path for the deep learning-based real-time quantitative microwave imaging for high-contrast scatterers.

In this article, a miniaturized dual-band dual-polarized slot antenna array is proposed for base station applications. It consists of two closely located $1 \times 4$ subarrays for the digital cellular system (DCS) and wideband code division multiple access (WCDMA) operations. The band-notched slot antenna (BNSA) is designed and adopted as the subarray element with radiation-suppression characteristic at notch frequencies. The notch frequency for one subarray is designed at the center operating frequency of the other subarray. As a result, the radiation from DCS subarray could be effectively suppressed within the WCDMA band and vice versa, resulting in high isolation between two subarrays with a small separation distance. By using the artificial magnetic conductor (AMC) reflector, the array height could be reduced by half, as compared with the perfect electric conductor (PEC) counterpart. In addition, a four-way unequal power divider is designed for the array’s beam-pattern synthesis. For the demonstration, the proposed array is fabricated and measured. The measurement results show that the dual-band array achieves the impedance bandwidths of 1.65–1.88 and 1.89–2.22 GHz, the isolations over 25 dB, the realized boresight gains of 12.2–12.8 and 12.3–13.2 dBi, and the sidelobe levels below −18 dB. The results indicate that the proposed array is a promising candidate for base-station applications.

Graphene’s remarkable electrical, mechanical, thermal, and chemical properties have made this the frontier of many other 2-D materials a focus of significant research interest in the last decade. Many theoretical studies of the physical mechanisms behind these properties have been followed by those investing the graphene’s practical use in various fields of engineering. Electromagnetics, optics, and photonics are among these fields, where potential benefits of graphene in improving the device/system performance have been studied. These studies are often carried out using simulation tools. To this end, many numerical methods have been developed to characterize electromagnetic field/wave interactions on graphene sheets and graphene-based devices. In this article, most popular of these methods are reviewed and their advantages and disadvantages are discussed. Numerical examples are provided to demonstrate their applicability to real-life electromagnetic devices and systems.

Edge states in topological photonic systems have the robust unidirectional propagation feature which originates from the topological nature of the bulk band dispersion. In this work, we propose a topological photonic crystal (PC) waveguide that is formed by introducing an air gap in an all-dielectric PC with $C_{6v}$ symmetry. The dispersion of the line defect states is tunable by varying the width of the air gap. Based on their field distributions, the states can be classified into even- and odd-symmetric states. The even-symmetric states are found to be the nontrivial topological edge states and exhibit pseudospin-locking unidirectional propagation property. By introducing disorders to the waveguide, these states are proven to be robust with well suppressed backscattering.

In this letter, a new deep learning (DL) approach is proposed to solve the electromagnetic inverse scattering (EMIS) problems. The conventional methods for solving inverse problems face various challenges including strong ill-conditions, high contrast, expensive computation cost, and unavoidable intrinsic nonlinearity. To overcome these issues, we propose a new two-step machine learning based approach. In the first step, a complex-valued deep convolutional neural network is employed to retrieve initial contrasts (permittivities) of dielectric scatterers from measured scattering data. In the second step, the previously obtained contrasts are input into a complex-valued deep residual convolutional neural network to refine the reconstruction of images. Consequently, the EMIS problem can be solved with much higher accuracy even for high-contrast objects. Numerical examples have demonstrated the capability of the newly proposed method with the improved accuracy. The proposed DL approach for EMIS problem serves a new path for realizing real-time quantitative microwave imaging for high-contrast objects.

This article investigates the impact of institutional difference and natural resource endowment in developing host countries on the location choice of Chinese OFDI. We found that institutio...

In this paper, we utilize the deep learning approach for the subwavelength imaging in far-field, which is realized by the near-field resonant metalens at microwave frequencies. The resonating metalens consisting of split-ring resonators (SRRs) are equipped with the strong magnetic coupling ability and can convert evanescent waves into propagating waves using the localized resonant modes. The propagating waves in the far-field are utilized as the input of a trained deep convolutional neural network (CNN) to realize the imaging. The training data for establishing the deep CNN are obtained by the EM simulation tool. Besides, the white Gaussian noise is added into the training data to simulate the interference in the real application scenario. The proposed CNN composes of three pairs of convolutional and activation layers with one additional fully connected layer to realize the recognition, i.e., the imaging process. The feasibility of utilizing the trained deep CNN for imaging is validated by numerical benchmarks. Distinguished from the subwavelength imaging methods, the spatial response and Green's function need not be measured and evaluated in the proposed method.

In this letter, a novel absorbing boundary condition (ABC) computation method for finite-difference time-domain (FDTD) is proposed based on the machine learning approach. The hyperbolic tangent basis function (HTBF) neural network is introduced to replace traditional perfectly matched layer (PML) ABC during the FDTD solving process. The field data on the interface of conventional PML are employed to train HTBF-based PML model. Compared to the conventional approach, the novel method greatly decreases the size of a computation domain and the computation complexity of FDTD because the new model only involves the one-cell boundary layer. Numerical examples are provided to benchmark the performance of the proposed method. The results demonstrate that the newly proposed method could replace conventional PML and could be integrated into FDTD solving process with satisfactory accuracy and compatibility to FDTD. According to our knowledge, this proposed model combined artificial neural network (ANN) model is an unreported new approach based on a machine learning based for FDTD.

In this letter, we present a wideband planar antenna with on-demand band-rejected characteristics based on the peelable double electric-LC (DELC) resonator membranes. By applying microfabrication techniques, the subwavelength DELC structure is completely encapsulated in a transparent and flexible thin film with a total thickness of 10 $\mu$ m. Resonators with four different widths (4.0, 3.6, 3.2, 2.8 mm) are packaged as a solution kit, providing the rejection bands of 4.24–5.11, 4.61–5.38, 4.85–5.48, and 5.20–5.70 GHz, respectively. Owing to the passive and detachable features of this functional sticker, no biasing network is needed for the rejection band's on / off transition and the membrane could tolerate 1 mm horizontal mismatch and 10 $^\circ$ rotational mismatch during assembly. This work provides a comprehensive solution for the design, manufacture, and implementation of a bias-free wideband antenna with on-demand rejection band and motivates the development of an effective and compact anti-interference system.

A single-layer two-pole dual-band filtering antenna (DBFA) with orthogonal polarizations in the two bands is presented in this letter. The DBFA is based on a common dual-mode T-shaped resonator (TR). The two modes of the common resonator each couple to one of the two orthogonally placed patches, resulting in required radiation. The TR is responsible for generation of three transmission zeroes (TZs) in frequency response corresponding to each polarization at the broadside: two of them being intrinsic TZs due to the TR and the third caused by far field interference of TR's radiation with that of the patch.The low profile microwave design has its two passbands operating at 4.13 and 4.7 GHz (resulting in a frequency ratio of 1.14) with 10 dB return loss bandwidths of 1.2% and 2.9%, respectively.

Background: This study aimed to investigate the clinical and pathological characteristics and the profile of and temporal changes in glomerular diseases in 2403 paediatric renal biopsies from 1999 to 2019.Methods: Renal biopsies performed on children aged ≤18 years between 1999 and 2019 were analysed at our centre. We analysed the clinical and histological characteristics, distribution of paediatric renal diseases with various clinical presentations, and changes in the pattern of kidney disease during the study period.Results: The most common primary glomerular disease was IgA nephropathy (IgAN) (24.3%), followed by minimal change disease (MCD) (15.3%) and membranous glomerulonephritis (MN) (13.1%). Henoch-Schonlein purpura nephritis (HSPN) (18.1%) and lupus nephritis (LN) (7.2%) were the most frequently recorded secondary glomerular diseases. Alport syndrome and thin basement membrane nephropathy (TBMN) were the most common inherited glomerular diseases, accounting for 1.2% and 0.6% of the total glomerular diseases in children, respectively. The number of boys with IgAN, MCD and IgM nephropathy (IgMN) was significantly higher than that of girls, while the number of girls with MN and LN was significantly higher than that of boys. The frequencies of MCD, MN, IgMN and endocapillary proliferative glomerulonephritis (EnPGN) in the 13-18-year-old group were significantly higher than those in the 0-12-year-old group, while the frequencies of IgAN, mesangial proliferative glomerulonephritis (MsPGN) and focal proliferative glomerulonephritis (FPGN) were lower than those in the 0-12-year-old group. The ratio of Alport syndrome and TBMN in the 0-12-year-old group was significantly higher than that in the 13-18-year-old group. The proportion of patients with MCD and MN in 2010-2019 was significantly higher than that in 1999-2009, while the ratio of IgAN, MsPGN, IgMN, EnPGN, membranoproliferative glomerulonephritis (MPGN), HSPN and HBV-associated glomerulonephritis (HBV-GN) decreased. MCD (28.5%) was the most common cause of nephrotic syndrome (NS). In children with haematuria and proteinuria, HSPN (38.8%) and IgAN (36.9%) were more common than other glomerular diseases. IgAN (39.4%) was the most common cause of AKI. Sclerosing glomerulonephritis (SGN) (21.1%) was the main cause of progressive chronic kidney disease (CKD).Conclusions: Glomerular diseases in children were related to sex and age. From 1999 to 2019, the spectrum of children's kidney disease in our centre changed significantly.

Structured light characterized by spatially inhomogeneous optical fields found rich applications in optical communication, sensing, microscopy, manipulation, and quantum information. While generation of structured light has been extensively studied in linear optics, the nonlinear optical process, particularly in two-dimensional (2D) materials, is an emerging alternative for generating structured light at shorter wavelengths. In this work, we theoretically demonstrate that radially and azimuthally polarized beams and vortex beams carrying orbital angular momentum could be generated at second-harmonic frequencies by using 2D material-based metasurfaces comprising the same transition-metal dichalcogenide meta-atoms. Manipulation of translations and orientations of anisotropically nonlinear meta-atoms exhibiting a threefold rotation-symmetrical crystalline structure induces strong nonlinear spin-orbital coupling, which enables simultaneous control of spatial phase and polarization in second-harmonic generation. The nonlinear transition-metal dichalcogenide metasurface proposed is promising for on-chip integration of nonlinear generation of structured light.

Recent advances in the pathophysiologic understanding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has indicated that patients with severe coronavirus disease 2019 (COVID-19) might experience cytokine release syndrome (CRS), characterized by increased interleukin (IL)-6, IL-2, IL-7, IL-10, etc. Therefore, the treatment of cytokine storm has been proposed as a critical part of rescuing severe COVID-19. Several of the cytokines involved in COVID-19 employ a distinct intracellular signaling pathway mediated by Janus kinases (JAKs). JAK inhibition, therefore, presents an attractive therapeutic strategy for CRS, which is a common cause of adverse clinical outcomes in COVID-19. Below, we review the possibilities and challenges of targeting the pathway in COVID-19., Highlights Recent advances in the pathophysiologic understanding of COVID-19 infection have suggested a critical role of cytokine release syndrome (CRS) in severe COVID-19 patients. Several inflammatory cytokines that are involved in CRS and correlate with adverse clinical outcomes in COVID-19 employ a distinct intracellular signaling pathway mediated by Janus kinases (JAKs). JAK-STAT signaling may be an excellent therapeutic target for the development of much needed therapies for COVID-19.

We demonstrate the coexistence of pseudospin- and valley-Hall-like edge states in a photonic crystal with $C_{3v}$ symmetry, which is composed of three interlacing triangular sublattices with the same lattice constants. By tuning the geometry of the sublattices, three complete photonic band gaps with nontrivial topology can be created, one of which is due to the band inversion associated with the pseudospin degree of freedom at the $\Gamma$ point and the other two due to the gapping out of Dirac cones associated with the valley degree of freedom at the $K, K'$ points. The system can support tri-band pseudospin- and valley-momentum locking edge states at properly designed domain-wall interfaces. Furthermore, to demonstrate the novel interplay of the two kinds of edge states in a single configuration, we design a four-channel system, where the unidirectional routing of electromagnetic waves against sharp bends between two routes can be selectively controlled by the pseudospin and valley degrees of freedom. Our work combines the pseudospin and valley degrees of freedom in a single configuration and may provide more flexibility in manipulating electromagnetic waves with promising potential for multiband and multifunctional applications., Comment: 6 pages, 5 figures

Recently, electromagnetic (EM) beams with the orbital angular momentum (OAM) have been explored for multiplexing in communication systems. Each OAM mode is encoded with data and can be identified by the OAM index, namely the topological charge. So far, the amplitude of OAM mode is gaining more attention for its application as another modulation format. Therefore, it is of great importance to accurately extract both the OAM index and corresponding amplitude. In this paper, we propose a modified dynamic mode decomposition (DMD) approach for the analysis of OAM modes. It is shown that not only topological charges but also high-resolution amplitude patterns of both single OAM mode and composite OAM modes can be obtained. The proposed approach provides an effective tool for the demultiplexing of OAM-carrying beams, especially in the case when the amplitude information is required.

In this letter, we introduce a novel beam scanning in a single-rectangular-patch antenna realized by coupled modes. The design exhibits radiated beams that scan as a function of frequency, but is different in its operation mechanism compared to a traditional leaky-wave antenna. The idea is to manipulate the phase difference between the fields at two radiating slots of the antenna to reform the beam. Metal vias are introduced to create two coupled half-mode cavities in the patch antenna. The mutual coupling between the two cavities makes the phase difference as a function of the operating frequency. The simulated beam scans from broadside to 43 $^{\circ }$ within the 3 dB gain band. The implemented sample realizes 4.55% bandwidth of $S_{11}$ with center frequency at 5.05 GHz by measurement. The beam scans from 14 $^{\circ }$ to 34 $^{\circ }$ within the matching band, which is confirmed by both simulation and measurement. The measured radiation efficiency within the matching band is comparable to a regular-patch antenna.

A two-pole half-mode substrate integrated waveguide (HMSIW) cavity-based filtering antenna is presented. The HMSIW cavity is used as a radiating resonator with a conventional substrate integrated waveguide (SIW) cavity functioning as a high- $Q$ resonator of the filter, leading to its compact size. The concept of source-load coupling is introduced for filtering antennas, which allows for the presence of two controllable transmission zeroes (TZs) in the frequency response of proposed design. This is accomplished by using electric coupling between two resonator cavities and a combination of microstrip/coaxial line to feed the antenna. The single-layer printed circuit board structure provides a broadside gain of 4.3 dBi at the operating frequency of 5.5 GHz. Gain curves are plotted at the broadside of the antenna, clearly showing a quasi-elliptic response and a 3-dB bandwidth of 2.6%.

Radiation is a vital mechanism affecting electromagnetic interference (EMI), noise control, and performance optimization in today's electronic designs. Due to tight electromagnetic compatibility standards, it becomes increasingly important to diagnosis the radiation hot spot in the radiation process before the mitigation is applied. In this paper, the characteristic mode analysis has been implemented together with the integral equation based numerical methods to identify the hot spots for EMI radiation. During this process, the current is split into radiating and nonradiating ones. The radiated power from each part of the structure can be quantified using the radiating current. Therefore, the radiation hot spot can be identified. Several numerical examples are applied to benchmark the proposed approach. This paper provides a guideline in discovering radiation related geometrical features, and designing methodologies for real geometries.

In this paper, a discontinuous Galerkin time-domain (DGTD) method is developed to analyze the power-ground planes taking into account the decoupling capacitors. In the presence of decoupling capacitors, the whole physical system can be split into two subsystems: 1) the field subsystem that is governed by Maxwell’s equations that will be solved by the DGTD method, and 2) the circuit subsystem including the capacitor and its parasitic inductor and resistor, which is going to be characterized by the modified nodal analysis algorithm constructed circuit equations. With the aim to couple the two subsystems together, a lumped port is defined over a coaxial surface between the via barrel and the ground plane. To reach the coupling from the field to the circuit subsystem, a lumped voltage source calculated by the integration of electric field along the radial direction is introduced. On the other hand, to facilitate the coupling from the circuit to field subsystem, a lumped port current source calculated from the circuit equation is introduced, which serves as an impressed current source for the field subsystem. With these two auxiliary terms, a hybrid field-circuit matrix equation is established, which enables the field and circuit subsystems are solved in a synchronous scheme. Furthermore, the arbitrarily shaped antipads are considered by enforcing the proper wave port excitation using the magnetic surface current source derived from the antipads supported electric eigenmodes. In this way, the S-parameters corresponding to different modes can be conveniently extracted. To further improve the efficiency of the proposed algorithm in handling multiscale meshes, the local time-stepping marching scheme is applied. The proposed algorithm is verified by several representative examples.

Proper power integrity (PI) analysis is required for printed circuit board (PCB) power distribution network (PDN) design. Top-layer interconnect inductance for PI has always been a vital concern for high-speed industry. Developing a simple physics-based equivalent circuit model for critical structures is essential for understanding the physics of the system and for intelligent designs. In this paper, a physics-based model size reduction (PMSR) method is applied to get the equivalent circuit model for the above-ground geometries. The extracted physics-based models are also based on the partial element equivalent circuit (PEEC) method, and can be used in analyzing the structure in its parts. By applying PMSR method, a physics-based equivalent circuit model can be proposed and this circuit model is related to the geometric features of the design. In this way, PMSR method can provide an intuitive guideline in designing PCB and reducing above inductances, therefore, a low-ripple dc voltage can be delivered through PDN. Taking advantage of PEEC and PMSR methods, the top-layer inductances of three different geometries are calculated and the physics-based circuit models are obtained, respectively.

This letter presents a novel high-impedance surface (HIS)-based leaky-wave antenna excited by collimated surface wave (SW). The proposed antenna consists of two identical SW launchers (SWLs) and an HIS structure. Regarding the SWL, it is based on an offset-fed parabolic reflector. By using the substrate-integrated waveguide technique, the reflector system is integrated in the planar substrate. For the HIS, it is formed by a periodically arranged rectangular microstrip patch array. The proposed SWL can generate collimated SW with the $\rm {TM_0}$ propagation mode. With the perturbation of the HIS, the guided SW can be transformed to $m$ = $-$ 1 space-harmonic-mode leaky wave. In addition, in order to obtain efficient broadside radiation, an additional secondary slit is properly designed in each unit cell of the HIS to suppress the open-stopband effect. A prototype of the proposed antenna is demonstrated by both full-wave simulation and experimental verification. Continuous beam scan can be realized from $-36^\circ$ to $+35.5^\circ$ within the frequency range of 16–22 GHz.

Electromagnetic (EM) waves with helical wavefront carry orbital angular momentum (OAM), which is associated with the azimuthal phase of the complex electric field. OAM is a new degree of freedom in EM waves and is promising for channel multiplexing in communication system. Although the OAM-carrying EM wave attracts more and more attention, the method of OAM generation at microwave frequencies still faces challenges, such as efficiency and simulation time. In this work, by using the circuit theory and equivalence principle, we build two simplified models, one for a single scatter and one for the whole metasurface to predict their EM responses. Both of the models significantly simplify the design procedure and reduce the simulation time. In this paper, we propose an ultrathin complementary metasurface that converts a left-handed (right-handed) circularly polarized plane wave without OAM to a right-handed (left-handed) circularly polarized wave with OAM of arbitrary orders and a high transmission efficiency can be achieved., Comment: 6 pages, 9 figures

This communication proposes a novel dual-beam dielectric grating antenna based on the supercell (SC) concept. Through the theoretical analysis of the effective phase constants of the SC, it is found that two space harmonic modes ( $m=-1$ and $m=-2$ ) can be simultaneously excited (above the air line) within a certain frequency range. This phenomenon leads to the generation of two radiation beams in the far-field region. At the frequency where the phase constants satisfy $\beta _{-1}=-\beta _{-2}$ , the two beams are in symmetric directions with respect to the axis that is perpendicular to the azimuth plane. Different from the conventional periodic structures that the $m=-2$ mode lacks well control, the proposed antenna can manipulate both modes and obtain equal performance for the two radiation beams. In this communication, the symmetric beam case is investigated. The detailed design principle is presented. In addition, the frequency-based beam steering characteristic that the two beams scan in the same clockwise or anticlockwise direction is discussed as well. The proposed antenna operates in 60-GHz band and it can be a good candidate for the WiGig application.

This paper proposes a new source reconstruction method (SRM) based on deep learning. The conventional SRM usually requires oversampled measurements data to ensure higher accuracy. Thus, conventional SRM numerical system is usually highly singular. A deep convolutional neural network (ConvNet) is proposed to reconstruct the equivalent sources of the target to overcome difficulty. The deep ConvNet allows us to employ less data samples. Besides, the ill-conditioned numerical system can be effectively avoided. Numerical examples are presented to demonstrate the feasibility and accuracy of the proposed method. Its performance is also compared with the traditional neural network and interpolation method. Moreover, we further expand the proposed method to measure the permittivity of dielectric scatterers.

Electromagnetics is based on the study of Maxwell's equations, which are the result of the seminal work of James Clerk Maxwell completed in 1865, after his presentation to the British Royal Society in 1864. It has been over 150 years ago now, and this is a long time compared to the recent leaps and bounds progress made in technological advancements. Nevertheless, electromagnetics is still being continuously researched and studied despite its age. The reason is that electromagnetics is extremely useful and has impacted a large sector of modern technologies.

A quasi-continuous composite perfect electric conductor-perfect magnetic conductor metasurface and a systematic metasurface design process are proposed for the orbital angular momentum (OAM) generation. The metasurfaces reflect the incident left circularly polarized (LCP)/right circularly polarized (RCP) plane wave to RCP/LCP vortex beams carrying OAM at normal or oblique direction. Unlike conventional metasurfaces that are composed of discrete scatterers, the scatterers on the proposed metasurface form a quasi-continuous pattern. The patterning of the metasurface is calculated through grating vectors, and no optimization of single scatterer is required. Furthermore, the distortions from local-response discontinuity of discrete scatterers are avoided. This letter provides great convenience to high-quality OAM generation., Comment: 5 pages, 8 figures

With the purpose of avoiding very fine mesh cells in the proximity of a thin wire, the modified telegrapher’s equations (MTEs) are employed to describe the thin wire voltage and current distributions, which consequently results in reduced number of unknowns and augmented Courant–Friedrichs–Lewy (CFL) number. As hyperbolic systems, both the MTEs and the Maxwell’s equations are solved by the discontinuous Galerkin time-domain (DGTD) method. In realistic situations, the thin wires could be either driven or loaded by circuit networks. The thin wire–circuit interface performs as a boundary condition for the thin wire solver, where the thin wire voltage and current used for the incoming flux evaluation involved in the DGTD-analyzed MTEs are not available. To obtain this voltage and current, an auxiliary current flowing through the thin wire–circuit interface is introduced at each interface. Corresponding auxiliary equations derived from the invariable property of characteristic variable for hyperbolic systems are developed and solved together with the circuit equations established by the modified nodal analysis (MNA) modality. Furthermore, in order to characterize the field and thin wire interactions, a weighted electric field and a volume current density are added into the MTEs and Maxwell–Ampere’s law equation, respectively. To validate the proposed algorithm, three representative examples are presented.

For surface features in short-wave infrared (SWIR, 1.3–3.0 μm) in remote sensing imagery, pixel values depict the total energy including reflection and emission. For surface features at normal temperature in SWIR band, emission energy can be ignored. While for surface features at high temperature in SWIR band, emission energy is equal to or even higher than the reflection energy. So remote sensing imagery of SWIR band can be used to separate emission and reflection energy as well as to realize temperature retrieval of high temperature targets. In this study, the seventh band (SWIR band) of Landsat8 OLI remote sensing imagery is used to perform the theoretical model research for temperature retrieval of high temperature targets. In the meantime, it is also used with the corresponding observation experiment of synchronization satellite to check the theoretical model. The result shows that the radiant flux density for mixed pixels with high temperature targets is higher than adjacent pixels without high temperature targets. Thus, the high temperature pixels can be identified in SWIR band. The retrieval results of temperature and fractional area for high temperature targets are consistent with reality. In the study, the result illustrates that it is effective to identify high temperature targets in remote sensing imagery of SWIR band and the model is appropriate for temperature retrieval use.

To meet the electromagnetic interference regulation, the radiated emission from device under test such as electronic devices must be carefully manipulated and accurately characterized. Instead of resorting to the direct far-field measurement, in this paper, a novel approach is proposed to model the radiated emission from electronic devices placed in shielding enclosures by using the near electric field only. Based on the Schelkkunoff's equivalence principle and Raleigh–Carson reciprocity theorem, only the tangential components of the electric field over the ventilation slots and apertures of the shielding enclosure are sufficient to obtain the radiated emissions outside the shielding box if the inside of the shielding enclosure was filled with perfectly electric conductor (PEC). In order to efficiently model wideband emission, the time-domain sampling scheme is employed. Due to the lack of analytical Green's function for arbitrary PEC boxes, the radiated emission must be obtained via the full-wave numerical methods by considering the total radiated emission as the superposition between the direct radiation from the equivalent magnetic currents in free space and the scattered field generated by the PEC shielding box. In this study, the state-of-the-art discontinuous Galerkin time-domain (DGTD) method is utilized, which has the flexibility to model irregular geometries, keep high-order accuracy, and more importantly involves only local operations. For open-region problems, a hybridized DGTD and time-domain boundary integration method applied to rigorously truncate the computational domain. To validate the proposed approach, several representative examples are presented and compared with both analytical and numerical results.

The electromagnetic (EM) characterization of graphene under general EM environments is becoming of interest in the engineering and scientific research fields. However, its numerical modeling process is extremely cost prohibitive due to the huge contrast between its thickness and other dimensions. In this work, for the first time, the EM features of graphene are characterized by a circuit model through the partial element equivalent circuit (PEEC) method. The atomically thick graphene is equivalently replaced by an impedance boundary condition. After incorporating the PEEC method, a novel surface conductivity circuit model is derived for graphene. A physical resistor and inductor are added into the conventional PEEC cell due to the dispersive conductivity property of graphene. The proposed novel method significantly reduces the memory and CPU time consumption for general graphene structures when compared with standard numerical finite element method (FEM) or finite difference (FD) methods, where 3-D meshing is unavoidable. This model also transforms the surface conductivity of graphene into a vivid circuit, and physical properties of the material can be conveniently obtained, such as radiation, scattering, and resistance properties, when compared with method of moments (MOM). In addition, the radiation and scattering calculation by MOM entail the cumbersome steps of defining a bounding surface and implementing a multidimensional integrand, while in PEEC, these complications are entirely bypassed by the concise vector–matrix–vector product (VMVP) formulas. To validate the introduced algorithm, various numerical examples are presented and compared with existing references.

Secondary brain damage caused by hyperactivation of autophagy and inflammatory responses in neurons plays an important role in hypoxic-ischemic brain damage (HIBD). Although previous studies have implicated Toll-like receptor 4 (TLR4) and nuclear factor kappa-B (NF-κB) in the neuroinflammatory response elicited by brain injury, the role and mechanisms of the TLR4-mediated autophagy signaling pathway in neonatal HIBD are still unclear. We hypothesized that this pathway can regulate brain damage by modulating neuron autophagy and neuroinflammation in neonatal rats with HIBD. Hence, we established a neonatal HIBD rat model using the Rice-Vannucci method, and injected 0.75, 1.5, or 3 mg/kg of the TLR4 inhibitor resatorvid (TAK-242) 30 minutes after hypoxic ischemia. Our results indicate that administering TAK-242 to neonatal rats after HIBD could significantly reduce the infarct volume and the extent of cerebral edema, alleviate neuronal damage and neurobehavioral impairment, and decrease the expression levels of TLR4, phospho-NF-κB p65, Beclin-1, microtubule-associated protein l light chain 3, tumor necrosis factor-α, and interleukin-1β in the hippocampus. Thus, TAK-242 appears to exert a neuroprotective effect after HIBD by inhibiting activation of autophagy and the release of inflammatory cytokines via inhibition of the TLR4/NF-κB signaling pathway. This study was approved by the Laboratory Animal Ethics Committee of Affiliated Hospital of Yangzhou University, China (approval No. 20180114-15) on January 14, 2018.

Two capacitor loaded planar resonators are introduced in a two-cavity substrate integrated waveguide (SIW) structure to obtain a fourth order filter. The planar resonators each produce a transmission zero by signal interference. Design methodology for a 5 % bandwidth bandpass filter operating at 2.35 GHz is presented in the paper. Two transmission zeroes are placed on either side of the filter passband to obtain a quasi-elliptic response with a mid-band inserion loss of 1.65 dB. Good agreement is obtained between measured and simulated responses of the single-layer printed circuit board (PCB) filter.

A new blazed metasurface grating for circularly polarized (CP) incident wave operating at 10 GHz is proposed. Such a structure can provide strong auto-collimation for the CP incident wave. Unlike the conventional scatterer, which typically reverses the handedness of the incident CP wave upon reflection, the proposed grating can preserve the handedness. The auto-collimation blazing effect and handedness preservation are achieved by a specially designed reactive impedance surface, which allows independent response controls to transverse electric (TE) and transverse magnetic (TM) polarizations. The proposed idea is demonstrated by simulations and verified by experiments. Comparisons with conventional sawtooth grating are made through measurements.

A composite perfect electric conductor (PEC)-perfect magnetic conductor (PMC) metasurface is proposed for orbital angular momentum (OAM) generation. Each scatterer on the metasurface consists of an anisotropic PEC layer and an isotropic PMC layer. Unlike conventional metasurfaces that composed of discrete scatterers, the scatterers on the proposed metasurface form a quasi-continuous pattern. Therefore, negative consequences of periodicity breaking from the patterned scatterers with varying sizes or orientations and their mutual coupling are avoided. We model the scatterer using Jones matrix. Its design is based on the features of PEC and PMC, which abandons complicated optimization process. The patterning of scatterers on the metasurface is determined by a grating function. The designed metasurface reflects the incident left circularly polarized (LCP)/right circularly polarized (RCP) plane wave to a RCP/LCP vortex beam carrying OAM, with nearly 100% efficiency.

In this paper, a novel translator calculation method for the multilevel fast multipole algorithm (MLFMA) is proposed based on a machine learning approach. The generalized regression neural networks are introduced to fit the translation function of MLFMA during the procedure of eletromagnetic scattering analysis. Compared to the traditional method, the new method inherits advantages of the generalized regression neural networks (GRNN) and can approximate the translator with high accuracy simultaneously. As an example, a two-level 2D MLFMA for a perfect electrically conductor (PEC) is finally implemented and the translators are reconstructed by using the proposed model. The numerical results validate the effectiveness of the proposed method.

In this paper, two novel computational processes are proposed to solve Finite-Difference Time-Domain (FDTD) based on machine learning deep neural networks. The field and boundary conditions are employed to establish recurrent neural network FDTD (RNN-FDTD) model and convolution neural network FDTD (CNN-FDTD) model respectively. Numerical examples from scalar wave equations are provided to benchmark the performance of the proposed methods. The results demonstrate that the newly proposed methods could solve FDTD steps with satisfactory accuracy. According to our knowledge, these are unreported new approaches for machine learning based FDTD solving methods.

Graphene plasmonics have attracted significant attention in the past few years due to the remarkable optical and electrical properties of graphene. A highly effective method based on surface integral equations (SIE) in the frequency domain is proposed to describe both linear and nonlinear effects of graphene efficiently and accurately. Graphene, a centrosymmet-ric material, can possess second harmonic generation (SHG) when the conductivity is nonlocal. In this work, the fundamental harmonic (FH) of a graphene wrapped particle is studied as the first benchmark by introducing a conducting surface in SIE. Then it is modified to analyze a graphene-based patch antenna in both FH and SHG. This method can be extended to other two-dimensional materials easily, and fast multipole algorithm can be applied to accelerate the simulation.