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Nowadays, pervasive vision through synthetic aperture radar (SAR) imaging sensors is a crucial part of air-borne and space-borne platforms to reach the concept of internet of multimedia things over satellites and visual flying ad-hoc networks. SAR sensors always need high-performance data reconstruction techniques to provide quality of experience for end-users of the distributed surveillance nodes and ensuring reliable decision-making in the autonomous vehicles. Using prior information in SAR image reconstruction, improves the quality of reconstructed image. Many sparse regularization methods use pre information terms in which the image is sparsely presented based on a predefined dictionary. However, if the desired features of the real image have not a sparse representation based on the predefined dictionary, image reconstruction with enhanced interested features will be failed. Dictionary learning to better adapt with the underlying scene can lead to better image reconstruction. On the other hand, using the idea of dictionary learning in the image reconstruction problem, and considering that the data used to train the dictionary may be incomplete and noisy, will create limitations for this method. In this paper, a new idea based on the use of an overcomplete dictionary consisting of a learned dictionary and a predefined dictionary (pre-learned dictionary) for SAR image reconstruction problem is presented. Developing the necessary mathematical relations and providing the framework for SAR image reconstruction based on the use of the overcomplete pre-learned dictionary, to simultaneously enhance the features considered in advance and the features associated with the image, from incomplete and noisy SAR raw data is presented in this article. We also present an iterative algorithm for solving the corresponding optimization problem. Simulation results based on the real data of TerraSAR-X and the Lynx airborne system show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Objection detection of vehicles and pedestrians in fog is of great significance for intelligent transportation and autonomous driving. Polarization image is beneficial to improve the object detection under adverse weather conditions. This study proposed a polarization image fusion method based on grouped convolutional attention network (GCAnet) to improve the object detection for cars and persons in foggy street scenes. Based on the international available Polar LITIS image dataset, a multi-channel grouped convolution matrix was first constructed to input different types of polarization images. Then, a grouped attention module was added to enhance the features in each type of polarization image, and finally each convolutional matrix was further connected to the detection network in series to perform objection detection. The experimental results prove that three types of polarization image fusion are obviously better than those of any two types of polarization image fusion and one single polarization image; and adding ECA attention module after multi-channel convolution can further enhance the accuracy of I04590 + Pauli + Stokes fused image to the highest value of 76.46%. The improvement of network lightweight shows that the Mobilenet-ECA has increased the speed by 26% with a slightly reduced accuracy. The proposed GCAnet method has significantly surpassed traditional objection detection networks of SSD300, SSD512, Faster R-CNN600, Yolov3, and Yolov4, which has increased the mAP@0.5 by 28.90%, 27.60%, 15.01%, 24.98%, and 16.45%, respectively; and has increased the mAP@0.5 by 9.36% and 6.20% compared to foggy image detection methods of AOD-Net SSD and DeRF-Yolov3-X, respectively. This work demonstrates the potential of GCAnet enabled polarization image fusion technology to be used as an effective foggy objection detection method in the field of intelligent transportation and autonomous driving. [ABSTRACT FROM AUTHOR]

There are inconsistent tasks and insufficient training in the SAR ship detection model, which severely limit the detection performance of the model. Therefore, we propose a twin branch network and design two loss functions: regression reverse convergence loss and classification mutual learning loss. The twin branch network is a simple but effective method containing two components: twin regression network and twin classification network. Aiming at the inconsistencies between training and testing in regression branches, we propose a regression reverse convergence loss (RRC Loss) based on twin regression networks. This loss can make multiple training samples in the twin regression branch converge to the label from the opposite direction. In this way, the test distribution can be closer to the training distribution after processing. For inadequate training in classification branch, Inspired by knowledge distillation, we construct self-knowledge distillation using a twin classification network. Meanwhile, our proposed classification mutual learning loss (CML Loss) enables the twin classification network not only to conduct supervised learning based on the label but also to learn from each other. Experiments on SSDD and HRSID datasets prove that, compared with the original method, the proposed method can improve the AP by 2.7–4.9% based on different backbone networks, and the detection performance is better than other advanced algorithms. [ABSTRACT FROM AUTHOR]

Urban floods can affect people's lives and properties, and therefore, urban flood mapping is crucial for reliable risk assessment and the development of effective mitigation strategies. With the advent of high spatial and temporal resolution satellite images, remote sensing has become popular for urban flood mapping. Synthetic aperture RADAR (SAR) sensors can capture image data during a flood event because their emitted signal can penetrate through the clouds. However, they have some limitations, such as layover, shadowing, and speckle noise, that might challenge their usage, especially for urban flood mapping. Deep learning (DL) algorithms have been widely used for automatic urban flood mapping using remote sensing data, but the flood mapping accuracy achieved using SAR and DL algorithms is still uncertain. This paper proposes a DL-based change detection framework, convolutional Siamese network (CSN), for flood mapping in three urban areas: parts of Ottawa, ON and Gatineau, QC, Abbotsford, BC, and Leverkusen, Germany. The datasets applied were Sentinel-1 and dual-polarized RADARSAT Constellation Mission (RCM) data. The applied data were captured in C-band, and their resolutions were 10 m and 5 m for Sentinel-1 and RCM, respectively. Comparison with other DL-based segmentation algorithms, including Unet, Unet++, DeepLabV3+, and Siamese-Unet, confirmed the reliability of the proposed CSN. Although a promising flood recall rate of about 0.7 was achieved, it was inferred from the flood precision and F1 score that Sentinel-1 data medium resolution might hinder its application for urban flood mapping. Further, RCM data were also tested in both urban and non-urban areas, and a precision of 0.79 was achieved for the non-urban case. Experiments on two existing datasets, SEN12FLOOD and SEN1FLOOD11, showed that the proposed CSN achieved a higher precision index of 0.75 on SEN12-FLOOD than SEN1FLOOD11 dataset, with a precision of 0.2, because of different labeling formats between the two datasets. [ABSTRACT FROM AUTHOR]

The objective of this article is to describe a compact 4-port MIMO planar antenna with a high axial ratio bandwidth (ARBW) that is suitable for usage in 5G applications that operate at frequencies lower than 6 GHz. The optimized dimension of the proposed antenna element is 37 × 30 × 0.8 mm3 and FR-4 substrate has been used as a dielectric material with relative permittivity of 4.4, and a height of 1.6 mm. The proposed antenna has an impedance bandwidth (− 10 dB) in the range of 3.3–4.3 GHz (Simulated)/3.4–4.7 GHz (measured), with a 3-dB ARBW of 3.0–4.4 GHz (simulated)/3.0–4.0 GHz (measured) respectively. The configuration that has been suggested for a MIMO antenna consists of a single entity that has a radiating element in the shape of a T and a ground plane in the shape of a C, both of which are co-planar. The findings of the simulation are then validated by the measurement results which are carried out by using the VNA55071C Vector network analyzer. The suggested module has the potential to serve as a MIMO antenna for impending fifth-generation wireless applications as it achieves an isolation level of better than 15 dB, has an envelope correlation coefficient (ECC) of less than 0.005, and has a diversity gain (dB) > 9.95 dB. [ABSTRACT FROM AUTHOR]

The high-altitude imaging capabilities of Unmanned Aerial Vehicles (UAVs) offer an effective solution for maritime Search and Rescue (SAR) operations. In such missions, the accurate identification of boats, personnel, and objects within images is crucial. While object detection models trained on general image datasets can be directly applied to these tasks, their effectiveness is limited due to the unique challenges posed by the specific characteristics of maritime SAR scenarios. Addressing this challenge, our study leverages the large-scale benchmark dataset SeaDronesSee, specific to UAV-based maritime SAR, to analyze and explore the unique attributes of image data in this scenario. We identify the need for optimization in detecting specific categories of difficult-to-detect objects within this context. Building on this, an anchor box optimization strategy is proposed based on clustering analysis, aimed at enhancing the performance of the renowned two-stage object detection models in this specialized task. Experiments were conducted to validate the proposed anchor box optimization method and to explore the underlying reasons for its effectiveness. The experimental results show our optimization method achieved a 45.8% and a 10% increase in average precision over the default anchor box configurations of torchvision and the SeaDronesSee official sample code configuration respectively. This enhancement was particularly evident in the model's significantly improved ability to detect swimmers, floaters, and life jackets on boats within the SeaDronesSee dataset's SAR scenarios. The methods and findings of this study are anticipated to provide the UAV-based maritime SAR research community with valuable insights into data characteristics and model optimization, offering a meaningful reference for future research. [ABSTRACT FROM AUTHOR]

We present new radar images and polarimetric data for the candidate landing sites of the Russian Luna-25 spacecraft near the Manzinus and Boguslawsky craters in the south polar region of the Moon. The images were obtained with the 64-m TNA-1500 antenna at the Bear Lakes Satellite Communications Center of the Special Design Bureau of the Moscow Power Engineering Institute and the 13.2-m RT-13 radio telescope at the Svetloe Observatory of the Institute of Applied Astronomy of the Russian Academy of Sciences in a bistatic configuration at a wavelength of 4.2 cm. At this wavelength the radar signals can penetrate into the lunar regolith to a depth up to 1 m and are sensitive to surface and suspended rocks with a diameter of about 1 cm or more. A spatial resolution m per pixel was achieved through the focused processing algorithm that avoids the radar image smearing at a long integration time. The receiving-system noise temperature measurements during the entire observation session provided a reliable estimate of the circular polarization ratio (CPR) of the echo signal. Analysis of the radar images obtained revealed regions with high radar backscatter and CPR. The number and distribution of rocks and irregularities with sizes comparable to the radar wavelength on the surface and in the near-surface layer of regolith were estimated. As a result of the radar data analysis, we conclude that the surface and the near-surface regolith layer of the main site are smoother than those of the reserved site, which makes it preferable for landing. Thus, the resulting new radar images and CPR maps can be used in planning future lunar missions. [ABSTRACT FROM AUTHOR]

A high-speed, dual-plane, stereoscopic particle image velocimetry technique was complemented by a flow estimation method to construct three-dimensional Simple Frigate Ship 2 airwakes. In particular, three pairs of mutually-orthogonal streamwise and spanwise planes were measured, with the ultimate goal of simultaneously estimating various spanwise planes using an invariant streamwise plane. First, the dual-plane measurements were divided into training and test sets. Then, for each pair of planes in the training set, the large-scale structures spanning both (streamwise and spanwise) planes were learned using the proper orthogonal decomposition (POD) spatial modes. Next, in the test set, only the streamwise plane was assumed to be known, and the POD temporal modes (corresponding to the learned spatial modes) were estimated to construct low-order models of each spanwise plane. This approach found excellent agreement between the measured and estimated low-order spanwise planes, as evaluated by three metrics. Ultimately, the velocities across three spanwise planes were simultaneously calculated, demonstrating the experimental framework's ability to perform time-dependent, three-dimensional, low-order reconstruction of complex turbulent flows. [ABSTRACT FROM AUTHOR]

Surface quality control is a crucial part of rail manufacturing. Deep neural networks have shown impressive accuracy in rail surface defect segmentation under the assumption that the test images have the same distribution as the training images. However, in practice detection, the rail images exhibit variations in appearance and scale for different rail types and production conditions. Directly deploying the deep neural network on unseen images shows a performance degradation due to the distribution discrepancies of training images. To this end, we propose a cross-scale fusion and domain adversarial network (CFDANet) to improve the generalization ability of deep neural networks on unseen datasets. To alleviate the domain shift caused by defect scale differences, we design a dual-encoder to extract multi-scale features from images of different resolutions. Then, those features are adaptively fused through a cross-scale fusion module. For the domain shift caused by inconsistent rail appearance, we introduce transferable-aware domain adversarial learning to extract domain invariant features from different datasets. Moreover, we further propose a transferable curriculum to suppress the negative impact of images with low transferability. Experimental results show that our CFDANet can accurately segment defects in unseen datasets and surpass other state-of-the-art domain generalization methods in all five target domain settings. The source code is released at https://github.com/dotaball/railseg_dg. [ABSTRACT FROM AUTHOR]

A large number of modern functional single crystals of the middle category belong to gyrotropic media. In these crystals, when light propagates along the optical axis, rotation of the plane of its polarization is observed. In this study a spectrophotometric method is used to obtain the dispersion dependences of the rotation angle of the polarization plane. This method is based on measuring the intensity of the light passing through the polarizer–crystal–analyzer system. The crystal is a polished plane-parallel plate of a uniaxial gyrotropic crystal cut perpendicularly to the optical axis. Measurements are carried out on a Cary-5000 UV-Vis-NIR spectrophotometer in the wavelength range of 200–1200 nm using polarizers Glan–Taylor prisms. Polished plane-parallel plates of known SiO2 and α-LiIO3 crystals are used as samples. The obtained dispersion dependences of the spectral transmission coefficients have an oscillating character. The discrete values of the specific angles of rotation of the plane of polarization of light are calculated from the extrema on these dependences. These discrete values can be approximated by the Drude, Chandrasekhar, and Vyshin formulas, depending on what determines the nature of the rotational ability of the plane of polarization of light in each particular material. For the studied crystals the dependences of the modified Drude formula of the form 1/ρ = f(λ2), which should have a linear character in the case of an ideal crystal, are plotted. The obtained experimental results are closely correlated to the available published data. The advantages of this method lie in its efficiency, the possibility of obtaining dispersion dependences of the specific rotation angle of the polarization plane, the need for a single sample, the possibility of assessing the nature of the rotational ability of specific crystals, and the possibility of evaluating the structural perfection of the studied crystals. [ABSTRACT FROM AUTHOR]

The latest results of the most detailed analysis of multi-epoch polarization-sensitive observations of active galactic nuclei (AGN) jets at parsecs scales by very long baseline interferometry (VLBI) reveal several characteristic patterns of linear polarization distribution and its variability [1, 2]. Some of the observed profiles can be reproduced by a simple model of a jet threaded by a helical magnetic field. However, none of the models presented to date can explain the observed polarization profiles with an increase in its degree towards the edges of the jet, and accompanied by a "fountain" type electrical vector pattern and its high temporal variability in the center. Based on simulations of the VLBI observations of relativistic jets, we show here that the observed transverse linear polarization profiles can be naturally produced in a model of jets precessing on ten-years scales. In this scenario, due to the finite resolution of VLBI arrays, the initially strong polarization along the jet axis is blurred due to the superposition of regions whose polarization angle changes significantly when projected onto the sky plane. In our simulations, we qualitatively reproduce the distribution of the electric vector and its variability, though the polarization distribution images are characterized by a bright spine due to weak suppression of polarized emission, which is poorly consistent with observations of quasars. More effective depolarization can be obtained in models with the suppressed emission of the jet spine. [ABSTRACT FROM AUTHOR]

Building misinformation resilience at scale continues to pose a challenge. Gamified "inoculation" interventions have shown promise in improving people's ability to recognize manipulation techniques commonly used in misinformation, but so far few interventions exist that tackle multimodal misinformation (e.g., videos, images). We developed a game called Cat Park, in which players learn about five manipulation techniques (trolling, emotional manipulation, amplification, polarization, and conspiracism), and how misinformation can spread through images. To test the game's efficacy, we conducted a conceptual replication (N = 380) of Roozenbeek and van der Linden's 2020 study about Harmony Square, with the same study design, item set, and hypotheses. Like the original study, we find that people who play Cat Park find misinformation significantly less reliable post-gameplay (d = 0.95, p < 0.001) compared to a control group, and are significantly less willing to share misinformation with people in their network (d = 0.54, p < 0.001). These effects are robust across different covariates. However, unlike the original study, Cat Park players do not become significantly more confident in their ability to identify misinformation (p = 0.204, d = − 0.13). We did not find that the game increases people's self-reported motivation and confidence to counter misinformation online. [ABSTRACT FROM AUTHOR]

In this research, a uniplanar ground-centered MIMO with four ports is suggested for sub-6 GHz 5G NR bands with dual polarization. Four T-shaped antennas and a shared rectangular ground are the components of a uniplanar common ground MIMO system, and no decoupling components are employed for isolation. Because of their straightforward construction and ease of integration into handsets, uniplanar configurations are being used. The MIMO antennas cover the bandwidth of 3.37 GHz with a mid-frequency of 4.5 GHz covering the entire sub-6 GHz mid-band frequencies ranges from 3 to 6.37 GHz including the NR bands of n46/n47/n48/n77/n78/n79. The proposed uniplanar MIMO functions with dual polarization modes where 23.44% of the functioning bandwidth operates in circular polarization (CP) mode and the remaining 76.56% work in linear polarization mode. An isolation value of − 12.5 dB to − 34 dB has been achieved. With the value of diversity gain = 10 dB, error control code < 0.03, total active reflection coefficient < − 8 dB, and MEG < − 3 dB, the ground-centered MIMO adequately performs diversity. To confirm that the suggested MIMO is a suitable 5G handset system, the complete configuration is assessed for the users' left-hand and dual-hand specific absorption rate influences. The maximum gain attained by the suggested system is 4.35 dBi without the SAR effect and 7.7 dBi with the user dual-hand SAR effect. The suggested MIMO system offers 5G smartphones an effective single-layer rear cover implementation with large bandwidth and reduced SAR. [ABSTRACT FROM AUTHOR]

A dual-port multiple-input multiple-output (MIMO) filtenna with minimal sizes of 80 × 45 mm2 is set up in this study. Each element in this MIMO filtenna is positioned orthogonally to the one next to it to improve isolation. For the MIMO element to achieve high-frequency selectivity and compact size, a frequency-reconfigurable filtenna that was created by fusing a band-pass filter and a monopole radiator was used. The suggested filtenna can switch between its C-band and X-band operating states with ease. On build the filtenna circuit, a band-pass filter based on defective microstrip structure is inserted to a circular monopole radiator. The developed filtenna operates in the C-band frequency range of 6.5–8 GHz and the X-band frequency range of 8–12 GHz. It is possible to use the X-band operating state for communication in a cognitive radio environment. Used as a decoupling structure, metamaterial structures can increase isolation to more than 40 dB across the bandwidth. The suggested MIMO filtenna system has an envelope correlation coefficient of 2.4e−6, a peak gain of 6 dBi, and an impedance bandwidth of 7.4–7.75 GHz. The MIMO filtenna is constructed and measured, and the findings of the measurement and simulation are in good agreement. [ABSTRACT FROM AUTHOR]

In this paper, a novel method for recoloring a textile image with polarization observation is proposed. By polarization image analysis, the proposed method can easily catch the specular reflection of yarns. Polarization image analysis also contributes to highly accurate region segmentation of warp and weft yarns. The conventional method using convex-hull assumes that an image is composed of at least four color elements. Our proposed method can overcome the limitations of too few textile colors. Our method can process textile images composed of only two color elements while existing methods struggle. In addition, we show how to generate images recolored both correctly and naturally through interactive alpha-matting, instead of aiming only at efficiency in recoloring, which sometimes results in unnatural images. A user study is performed to test the GUI indicators and the naturalness of the recoloring results. Extensive experiments show that the proposed method generates far better textile recoloring results compared to existing approaches. [ABSTRACT FROM AUTHOR]

In this paper, we provide a precise description of the compatibility conditions for the initial data so that one can show the existence and uniqueness of regular short-time solution to the Neumann initial-boundary problem of a class of Landau–Lifshitz–Gilbert system with spin-polarized transport, which is a strong nonlinear coupled parabolic system with non-local energy. [ABSTRACT FROM AUTHOR]

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates. [ABSTRACT FROM AUTHOR]

Cycle consistency conducts generative adversarial networks from aligned image pairs to unpaired training sets and can be applied to various image-to-image translations. However, the accumulation of errors that may occur during image reconstruction can affect the realism and quality of the generated images. To address this, we exploit a novel long and short cycle-consistent loss. This new loss is simple and easy to implement. Our dual-cycle constrained cross-domain image-to-image translation method can handle error accumulation and enforce adversarial learning. When image information is migrated from one domain to another, the cycle consistency-based image reconstruction constraint should be constrained in both short and long cycles to eliminate error accumulation. We adopt the cascading manner with dual-cycle consistency, where the reconstructed image in the first cycle can be cast as the new input to the next cycle. We show a distinct improvement over baseline approaches in most translation scenarios. With extensive experiments on several datasets, the proposed method is superior to several tested approaches. [ABSTRACT FROM AUTHOR]

In this work, the tunable dual-band split ring terahertz (THz) polarization converter is proposed based on Weyl semimetals (WSMs). By changing the chemical potential of the WSMs, the polarization converter can realize the frequency-dependent linear–linear and circular–circular cross-polarization conversion in the two bands of 1.21–1.29 THz and 1.97–2.04 THz, respectively. The achieved polarization converter ratio (PCR) is higher than 99% for the two types of cross polarizations. Besides, the WSM-based polarization conversion also shows 2π phase shift and amplitude modulation by rotating the azimuth angles of the split ring. Furthermore, the 3-bit coding metasurfaces can achieve tunable linear–linear, circular–circular, and linear–circular beam modulation by adjusting the chemical potential of the WSMs. The proposed tunable metasurface would have wide applications in multiband cross-polarizations and different types of wave modulation with linear–linear, circular–circular, and linear–circular. [ABSTRACT FROM AUTHOR]

Context: Scientific data reduction on-board deep space missions is a powerful approach to maximise science return, in the absence of wide telemetry bandwidths. The Polarimetric and Helioseismic Imager (PHI) on-board the Solar Orbiter (SO) is the first solar spectropolarimeter that opted for this solution, and provides the scientific community with science-ready data directly from orbit. This is the first instance of full solar spectropolarimetric data reduction on a spacecraft. Methods: In this paper, we analyse the accuracy achieved by the on-board data reduction, which is determined by the trade-offs taken to reduce computational demands and ensure autonomous operation of the instrument during the data reduction process. We look at the magnitude and nature of errors introduced in the different pipeline steps of the processing. We use an MHD sunspot simulation to isolate the data processing from other sources of inaccuracy. We process the data set with calibration data obtained from SO/PHI in orbit, and compare results calculated on a representative SO/PHI model on ground with a reference implementation of the same pipeline, without the on-board processing trade-offs. Results: Our investigation shows that the accuracy in the determination of the Stokes vectors, achieved by the data processing, is at least two orders of magnitude better than what the instrument was designed to achieve as final accuracy. Therefore, the data accuracy and the polarimetric sensitivity are not compromised by the on-board data processing. Furthermore, we also found that the errors in the physical parameters are within the numerical accuracy of typical RTE inversions with a Milne-Eddington approximation of the atmosphere. Conclusion: This paper demonstrates that the on-board data reduction of the data from SO/PHI does not compromise the accuracy of the processing. This places on-board data processing as a viable alternative for future scientific instruments that would need more telemetry than many missions are able to provide, in particular those in deep space. [ABSTRACT FROM AUTHOR]

The vehicle re-identification task aims to retrieve the same vehicle from multiple cameras. One of the challenges of this task is that images of different vehicles may look very similar under the same perspective, which affects the performance of vehicle re-identification tasks. Recent studies have shown that the attention mechanism is effective for vehicle re-identification, because it encourages models to focus on information related to the identity of the target rather than interference information such as background. In this paper, we first propose a dual-relational attention module (DRAM), which simultaneously constructs the importance of a feature point in the spatial and channel dimensions, and further models the attention of the feature point in the three-dimensional space. Then, we integrate the dual-relational attention module into a three-branch network, called dual-relational attention network (DRA-Net). In addition, to ensure that the network can extract a large number of diverse information, we add a non-similarity constraint in dual-relational attention network (DRA-Net) to make different branches focus on different locations in an image. In the experiments, our method is verified on two datasets (VeRi-776 and VehicleID), and the experimental results indicate that the proposed method is superior to several advanced methods. [ABSTRACT FROM AUTHOR]

Residual strains affect the properties and performance of composite components, therefore measuring and predicting them are important. The prediction of residual strains from a model can be achieved by two steps: the generation of a geometric ply map and the modelling based on that to predict 3D residual strains. A novel method for identifying the most effective algorithm for characterising fibre orientation for the geometric ply map using ultrasound C-scan data has been developed. Finite element models were generated based on the fibre-orientation data from three different algorithms: the Radon transform, 2D fast Fourier transform, and Sobel filter. The models were used to predict residual strains due to three different severities of in-plane fibre waviness induced in a set of 18 specimens. Stratified leave-one-out cross validation was applied to obtain optimum parameters for the three characterisation algorithms and to update the values of the coefficient of thermal expansion for the material. Residual strains on the surface of the specimens were obtained from calculations based on the out-of-plane displacements measured using a digital image correlation system. The predicted and measured residual strain maps were decomposed into feature vectors using orthogonal polynomials to reduce data dimensionality and make quantitative comparisons. The measured residual strains and the predictions based on models using optimised parameters showed good agreement. The differences in performance were quantified based on the accuracy of the predicted residual strains, which showed that the Radon transform performed best. [ABSTRACT FROM AUTHOR]

An integrated multifunctional light-sheet nanoscopy (iMLSN) combined with differential interference contrast, total internal reflection, epifluorescence, a super-resolution radial fluctuation-stream module, and a wavelength-dependent light sheet was developed to simultaneously realize the six-dimensional (6D) vector-valued (three coordinates + rotational dynamics (azimuth and elevation angles) + transport speed) tracking of anisotropic nanoparticles in single living cells. The wavelength-dependent asymmetric scattering of light by gold nanorods was used to trigger signals depending on the polarizer angle, and real-time photo-switching was achieved by turning the polarizer, obtaining a series of super-resolution images, and tracking using different polarization directions and two channels. This technique was employed to directly observe native gold nanorods (AuNRs; 5 nm diameter × 15 nm length) and surface-functionalized AuNRs during their endocytosis and transport at the upper and attaching side membrane regions of single living cells, revealing that the AuNRs bound to the membrane receptors. The nanorods were subsequently internalized and transported away from the original entry spots. Detailed dynamic information regarding the rotation properties and endocytosis speed during the transmembrane process was also acquired for each region. The developed technique can be considered useful for the real-time monitoring of intracellular transport at various regions in single living cells, as well as for 6D vector-valued non-fluorescence super-resolution imaging and tracking. [ABSTRACT FROM AUTHOR]

To form a radar image of the Earth's surface, a polarization-modulation method is implemented based on the use of probing signals with a linear rotating polarization plane. A model of an experimental setup that realizes this method is described. The results of experimental studies of radar images of the Earth's surface that were obtained from an AN-26 aircraft of the Groza-26 onboard radar station (radar) are presented. Radar images were obtained in the standard mode of the radar operation with a fixed vertical polarization of radiation and in the radiation mode when the polarization plane is linear and rotates at a given frequency. An increased radar contrast of extended objects, such as roads and railways, is observed on a radar image of the Earth's surface when using polarization-modulated probing signals. A relationship between the characteristics of received polarization-modulated signals and the polarization parameters of radar objects has been established, which allows one to substantiate the experimental results obtained. [ABSTRACT FROM AUTHOR]

Image deraining aims to restore the clean scenes of rainy images, which facilitates a number of outdoor vision systems, such as autonomous driving, unmanned aerial vehicles and surveillance systems. This paper proposes a high-resolution detail-recovering image deraining network (HDRD-Net) to effectively remove rain streaks and recover lost details, as well as improving the quality of derained images. HDRD-Net consists of three sub-networks. First, we combine the residual network and Squeeze-and-Excitation block for rain streak removal. Second, we integrate the Structure Detail Context Aggregation block into the detail-recovering network to extract detail features form rainy images. Third, a dual super-resolution reconstruction network is utilized to enhance the quality of derained images. In addition, we extend the Rain100 dataset by incorporating low-resolution rainy images to construct a new Rain100++ dataset for high-resolution image deraining. Experimental results on several datasets show that HDRD-Net outperforms state-of-the-art methods in terms of rain removal, detail preservation and visual quality. [ABSTRACT FROM AUTHOR]

As of today, dissolution Dynamic Nuclear Polarization (dDNP) is the only clinically available hyperpolarization technique for 13C-MRI. Despite the clear path towards personalized medicine that dDNP is paving as an alternative and/or complement to Positron Emission Tomography (PET), the technique struggles to enter everyday clinical practice. Because of the minute-long hyperpolarization lifetime after dissolution, one of the reasons lies in the need and consequent complexities of having the machine that generates the hyperpolarization (i.e. the dDNP polarizer) on site. Since some years, research groups are working to make hyperpolarization transportable. Two different methods have been developed that allow "freezing" of the nuclear spin state prior to samples extraction from the polarizer. Nevertheless, so far, all attempts of transport have been limited to a very small scale and to the level of proof-of-principle experiments. The main reason for that is the lack of adequate hardware, strategy, and control on most of the crucial parameters. To bridge the technical gap with PET and provide MRI facilities with hours long relaxing hyperpolarized compounds at controlled conditions, a new generation of low cost/small footprint liquid He cryostats equipped with a magnetically enforced cryogenic probe is needed. In this paper, we detail the theoretical and practical construction of a hyperpolarized samples transportation device small enough to fit in a car and able to hold a sample at 4.2 K for almost 8 h despite the presence of a cryogenically-demanding purpose-built probe that provides enough magnetic field upon insertion of the sample and NMR quality homogeneity at storage position. Should transportable hyperpolarization via DNP become a reality, we herein provide important details to make it possible. [ABSTRACT FROM AUTHOR]

In this work, a dual-band polarization converter is proposed based on a reflective metasurface. The metasurface is an appropriate anisotropic structure with a pair of mutually perpendicular symmetric axes x and y, and the reflection phase difference under x- and y-polarized incidences is very close to 90° in the two frequency ranges of 7.9–9.2 GHz and 12.4–25.2 GHz, so the metasurface can be used as a high-efficiency dual-band polarization converter to achieve both linear-to-circular (LTC) and circular-to-linear (CTL) polarization conversions in two separated frequency bands. The simulation and experimental results show that, when the dual-band polarization converter is under the incidence of u- and v-polarized waves, the reflected wave will be converted to a circular-polarized (CP) one in the two frequency bands of 7.78–9.38 GHz and 12.30–25.60 GHz, a dual-band LTC polarization conversion will be achieved with high-efficiency; in addition, under CP incidence, the reflected wave will be converted to a linear-polarized one in the two frequency bands of 7.76–9.39 GHz and 12.22–25.57 GHz, a dual-band CTL polarization conversion with almost the same working band and polarization conversion rate will be achieved. Therefore, the dual-band polarization converter has great potential application values in various polarization controlled devices. [ABSTRACT FROM AUTHOR]

The study of the polarization direction is crucial in the issue of restoring the spatial structure of the magnetic field in the active galaxy parsec-scale jets. But, due to relativistic effects, the magnetic field projected onto the celestial sphere in the source reference frame cannot be assumed to be orthogonal to the observed direction of the electric vector in the wave. Moreover, the local axis of the jet component may not coincide with its motion direction, which affects the observed polarization direction. In this article, we analyze the transverse to jet distributions of the electric vector in the wave, obtained as a result of modeling with different jet kinematic and geometrical parameters for a helical magnetic field with a different twist angle and for a toroidal magnetic field in the center, surrounded by a varying thickness sheath, penetrated by a poloidal field. We obtained: (1) the shape of the electric vector transverse distribution depends in a complex way on the angles of the jet axis and the velocity vector with the line of sight; (2) ambiguity in determining the twist direction of the helical magnetic field under using only the distributions of the electric vector in the wave; (3) both considered magnetic field topologies can reproduce both the "spine–sheath" polarization structure and individual bright features with the longitudinal to the jet axis polarization direction. [ABSTRACT FROM AUTHOR]

The topology and spin-orbital polarization of two-dimensional (2D) surface electronic states have been extensively studied in this decade. One major interest in them is their close relationship with the parities of the bulk (3D) electronic states. In this context, the surface is often regarded as a simple truncation of the bulk crystal. Here we show breakdown of the bulk-related in-plane rotation symmetry in the topological surface states (TSSs) of the Kondo insulator SmB6. Angle-resolved photoelectron spectroscopy (ARPES) performed on the vicinal SmB6(001)-p(2 × 2) surface showed that TSSs are anisotropic and that the Fermi contour lacks the fourfold rotation symmetry maintained in the bulk. This result emphasizes the important role of the surface atomic structure even in TSSs. Moreover, it suggests that the engineering of surface atomic structure could provide a new pathway to tailor various properties among TSSs, such as anisotropic surface conductivity, nesting of surface Fermi contours, or the number and position of van Hove singularities in 2D reciprocal space. Previous work exploring the robustness of topological surface states to perturbations has mostly focused on surfaces with the same atomic structure as the bulk. Here the authors demonstrate the effect of surface reconstruction on the topological surfaces on the (100) surface of SmB6. [ABSTRACT FROM AUTHOR]

We consider the direct problem of determination of axisymmetric residual stresses in a finite isotropic dielectric cylindrical body caused by the diagonal tensor of inconsistent eigenstrains whose components depend only on the radial coordinate. The parameters of the stress field are investigated by using the obtained solution of the problem. These parameters can be empirically found by the polarization-optical method as a result of sounding of the body with rays of polarized light in different directions and then used as input data for the inverse problems of nondestructive determination of the residual stress-strain state. We consider three sets of directions in the planes of space symmetry of the stress-strain state. For each set, we establish the integral relations connecting the values of the corresponding polarizationoptical parameters with the distributions of the components of stresses in a body in the direction of raysounding. We perform quantitative investigations of the polarization-optical parameters depending on the level of residual stresses and their gradients. The results of these investigations enable us to estimate the informativity of the empirical data that can be obtained as a result of ray-sounding of the cylinder along these three sets of directions. [ABSTRACT FROM AUTHOR]

Using a novel variant of polarized light microscopy for high-contrast imaging and quantification of unstained histology slides, the current study assesses the prognostic potential of peri-tumoral collagenous stroma architecture in 32 human stage III colorectal cancer (CRC) patient samples. We analyze three distinct polarimetrically-derived images and their associated texture features, explore different unsupervised clustering algorithm models to group the data, and compare the resultant groupings with patient survival. The results demonstrate an appreciable total accuracy of ~ 78% with significant separation (p < 0.05) across all approaches for the binary classification of 5-year patient survival outcomes. Surviving patients preferentially belonged to Cluster 1 irrespective of model approach, suggesting similar stromal microstructural characteristics in this sub-population. The results suggest that polarimetrically-derived stromal biomarkers may possess prognostic value that could improve clinical management/treatment stratification in CRC patients. [ABSTRACT FROM AUTHOR]

Quantum spin Hall insulators (QSHI) have been proposed to power several applications, many of which rely on the possibility to switch on and off the non-trivial topology. Typically this control is achieved through strain or electric fields, which require energy consumption to be maintained. On the contrary, a non-volatile mechanism would be highly beneficial and could be realized through ferroelectricity if opposite polarization states are associated with different topological phases. While this is not possible in a single ferroelectric material where the two polarization states are related by inversion, the necessary asymmetry could be introduced by combining a ferroelectric layer with another two-dimensional (2D) trivial insulator. Here, by means of first-principles simulations, not only we propose that this is a promising strategy to engineer non-volatile ferroelectric control of topological order in 2D heterostructures, but also that the effect is robust and can survive up to room temperature, irrespective of the weak van der Waals coupling between the layers. We illustrate the general idea by considering a heterostructure made of a well-known ferroelectric material, In2Se3, and a suitably chosen, easily exfoliable trivial insulator, CuI. In one polarization state the system is trivial, while it becomes a QSHI with a sizable band gap upon polarization reversal. Remarkably, the topological band gap is mediated by the interlayer hybridization and allows to maximize the effect of intralayer spin-orbit coupling, promoting a robust ferroelectric topological phase that could not exist in monolayer materials and is resilient against relative orientation and lattice matching between the layers. [ABSTRACT FROM AUTHOR]

Because Pancharatnam-Berry (PB) geometrical phase can only be generated in the co-polarized reflection coefficient under circular polarized (CP) incidence for a reflective metasurface, the design of a reflective PB coding metasurface must be based on an appropriate polarization conversion metasurface (PCM) which can achieve CP-maintaining reflection. In this work, to design a reflective 2-dit PB coding metasurface for radar cross section (RCS) reduction, an ultra-wideband PCM is proposed at first, numerical simulation shows that the PCM can realize ultra-wideband CP-maintaining reflection from 8.6 to 35.9 GHz; moreover, PB phase will be generated in its co-polarized reflection coefficient under CP incidence by rotating its unit structure. Thus, an ultra-wideband reflective 2-dit PB coding metasurface is constructed successfully based on the PCM. The simulation and experiment results show that the coding metasurface has excellent performance in RCS reduction under arbitrary polarized incidences, compared with a pure metallic plate with the same size, its RCS can be reduced more than 10 dB in the frequency band 8.2–35.2 GHz with a relative bandwidth of 124.4%, in addition, the RCS reduction performance is kept well when the incident angle is increased to 45°. [ABSTRACT FROM AUTHOR]

The multi-spectral image pairs composed of LIDAR and RGB images demonstrates more effective detection performance in complex traffic environments, such as low illumination, motion blur and strong noise, etc. However, there is still a lack of relevant research on how to better fuse the two modalities to improve the robustness and detection accuracy of the perception system for autonomous vehicles under the condition of low visible light image quality. In this paper, we proposed a dual-modal image quality aware deep neural network (DMIQADNN). We comprehensively compared and analyzed the adaptions of fusion architectures in the early, middle, late, and score stages. By comprehensively considering the detection accuracy and detection speed, the fusion architecture in the middle stage was selected. Besides, we developed an image quality assessment network (IQAN) to evaluate the image quality score for RGB images. The corresponding fusion weights for RGB sub-network and LIDAR sub-network were adaptively assigned by using the proposed fusion weight assignment function. Then based on the calculated fusion weights, the RGB and LIDAR sub-networks were adaptively merged via a data fusion sub-network. The RGB images in the KITTI dataset were processed by reducing illumination and adding motion blur and Gaussian noises to produce a modified dataset containing 7481 RBG-LIDAR image pairs, and the DNIQADNN was trained and tested by semi-automatic annotation. The experimental results on modified KITTI Benchmark and dataset collected by using our own developed autonomous vehicle validate the robustness and effectiveness of proposed method. The ultimate FPS and AP values of the DNIQADNN reach 27 and 39.1, which are superior to those of the state-of-the-art instance segmentation networks. [ABSTRACT FROM AUTHOR]

Tuning the band gap of ferroelectric materials to visible region without reducing the polarization can provide an ideal photovoltaic material for solar energy harvesting, significantly efficient than the conventional p–n junction-based cells. In the present work, we have tried to achieve this elusive goal by doping Mo at the Ti ionic site in proper ferroelectric PbTiO3 which is known to have very large polarization. A significant reduction of band gap is achieved from 3.14 eV (un-doped PbTiO3) to 2.41 eV for 10% Mo doping concentration. In this doping, Mo-4d states which are lower in energy than Ti-3d states introduce an intermediate state below conduction band edge leading to band gap reduction. Analysis of the XRD patterns reveals that the Mo-doped PbTiO3 retains tetragonal structure and tetragonality increases with increasing the doping concentration of Mo. It is also found that increase of Mo concentration in PbTiO3 tends to enhance the conductivity suitable for transport of charge carriers. This finding may help to discover and design optical perovskite oxides for light energy harvesting application. [ABSTRACT FROM AUTHOR]

Spectropolarimetric reconstructions of the photospheric vector magnetic field are intrinsically limited by the 180 ∘ ambiguity in the orientation of the transverse component. The successful launch and operation of Solar Orbiter have made the removal of the 180∘ ambiguity possible using solely observations obtained from two different vantage points. While the exploitation of such a possibility is straightforward in principle, it is less so in practice, and it is therefore important to assess the accuracy and limitations as a function of both the spacecrafts' orbits and measurement principles. In this work, we present a stereoscopic disambiguation method (SDM) and discuss thorough testing of its accuracy in applications to modeled active regions and quiet-Sun observations. In the first series of tests, we employ magnetograms extracted from three different numerical simulations as test fields and model observations of the magnetograms from different angles and distances. In these more idealized tests, SDM is proven to reach a 100% disambiguation accuracy when applied to moderately-to-well resolved fields. In such favorable conditions, the accuracy is almost independent of the relative position of the spacecraft with the obvious exceptions of configurations where the spacecraft are within a few degrees of co-alignment or quadrature. Even in the case of disambiguation of quiet-Sun magnetograms with significant under-resolved spatial scales, SDM provides an accuracy between 82% and 98%, depending on the field strength. The accuracy of SDM is found to be mostly sensitive to the variable spatial resolution of Solar Orbiter in its highly elliptic orbit, as well as to the intrinsic spatial scale of the observed field. Additionally, we provide an example of the expected accuracy as a function of time that can be used to optimally place remote-sensing observing windows during Solar Orbiter observation planning. Finally, as a more realistic test, we consider magnetograms that are obtained using a radiative-transfer inversion code and the SO/PHI Software siMulator (SOPHISM) applied to a 3D-simulation of a pore, and we present a preliminary discussion of the effect of the viewing angle on the observed field. In this more realistic test of the application of SDM, the method is able to successfully remove the ambiguity in strong-field areas. [ABSTRACT FROM AUTHOR]

This paper presents measurements using a dual-polarised radiometer operating at 93 GHz to detect ice or water on asphalt in laboratory conditions. The brightness temperatures of both H and V polarizations were measured for a dry surface, liquid water, and ice on asphalt at observation angles of 50° and 56°. The results presented in this paper demonstrate that the studied road conditions can be identified by the radiometer. The measurements are compared with a model and surface parameters, such as dielectric constant and roughness are fitted and compared to reference values. The experiments and results, described in this article, are the first steps towards the future installation of a polarimetric sensor on a moving vehicle for traffic safety. [ABSTRACT FROM AUTHOR]

Surface subsidence threatens the structural stability of ground facilities located in mining-induced subsidence areas. Clarifying and evaluating the influence of surface subsidence can inform the construction and maintenance of various ground facilities, such as buildings, roads, and bridges. In this paper, we investigated mining-induced surface subsidence and areas of potential damage in Yangquan City, Shanxi Province, by exploiting small-baseline set interferometric synthetic aperture radar (SBAS-InSAR) monitoring and geographic information system (GIS) techniques. More specifically, we first investigated the distributions of subsidence areas and subsidence rates in Yangquan City from June 16th, 2016, to December 1st, 2016, by exploiting SBAS-InSAR monitoring. We then classified ground facilities, such as buildings, highways and railways, and identified their distributions using spatial analysis using GIS. Finally, we integrated the results of the two techniques to evaluate the potential damages induced by surface subsidence for various ground facilities. We found that, overall, (1) surface subsidence has seriously developed in the Yangquan Mine and (2) some of the subsidence areas exist in facilities with high-level restrictions, such as high-rise buildings, highways, and railways, which may cause potential damage. Our work presented in this paper could be referred to and applied to other similar cases. [ABSTRACT FROM AUTHOR]

A novel multiband 2 × 2 dual-polarization antenna with couple of meander line structure is proposed for IoT connected devices. The MIMO antenna operates from 1.39 to 6.02 GHz with the gain of 7.35 dB and the return loss of less than −10 dB, within its effective bandwidth at both input ports. The proposed dual polarized antenna has a very high isolation of −27 dB between the input ports. The performance of 2 × 2 MIMO antenna is analyzed with respect to the correlation coefficient, channel capacity loss, diversity gain, mean effective gain and total active reflection co-efficient. For simulation, High Frequency Structure Simulation (HFSS) solver is used and it also calculates the MIMO antenna parameters. The projected antenna shows multiband operation with polarization diversity and high isolation among elements. It also offers a good mixture of coverage and capacity benefits, which is expected to support the future IoT connected devices. [ABSTRACT FROM AUTHOR]

An ultra-thin dual-band metamaterial absorber (DMMA) worked in S-band and X-band is proposed by this paper. It is polarization-insensitive to the incident wave and has high absorptivity under the wide incident angle. The proposed DMMA is designed based on a square ring (SR) and a double cross pattern (DCP) structure, and the thickness of the DMMA is merely 0.013 λ min . The calculation results indicate that the proposed DMMA has two absorption peaks at the frequency of 3.80 GHz and 8.63 GHz, and all its absorptivity can reach 99.99%, which is close to perfect absorption. The impedance matching is used to explain the absorption principle of the DMMA, and the electromagnetic resonance is used to reveal the absorbing mechanism. Also, the influence of various polarization angles, incident angles, and structure parameters on the absorption performance are discussed. The satisfactory properties of the DMMA can be applied in the fields of communication, meteorology, electromagnetic shielding, and earth satellites. [ABSTRACT FROM AUTHOR]

A novel tunable miniaturized band reject filter employing RF MEMS varactors is reported. Another tunable filter was reported by the authors to work in the Ka-band of frequencies. The present work refers to C-band application making it suitable for satellite and wireless links. Novelty of the work lies in introduction of tunability to such low frequency ranges, compactness in size, CMOS compatibility and more efficient optimized fabrications process. This level of miniaturization has not been achieved by others hitherto. A Coplanar Waveguide (CPW) on a silicon substrate consisting of a central strip conductor with semi-infinite ground planes on both sides is considered where two Complementary Split Ring Resonators (CSRRs) are in series connection on the signal line of CPW. To achieve tunability of the band reject filter, a MEMS bridge capacitor is put on the signal line of the CPW in shunt in either up or down state. The rejection of stop bands are around − 23.80 dB for down state and − 22.90 dB for up state, whereas the centre frequency is 6.5 GHz for down state and 8.1 GHz is for up state simulation and the corresponding measured data are 6.7 GHz (− 35.29 dB) and 8.0 GHz (− 42.90 dB) respectively. The frequency roll off is very sharp because of additional poles. [ABSTRACT FROM AUTHOR]

A polarization-modulation method for simultaneous determination of the navigation bearing and roll parameters of an aircraft from orthogonally linearly polarized beacon signals is studied. Signals are emitted simultaneously from two spatially separated points in the horizontal plane with known coordinates. Onboard the aircraft, the resulting vector signals are received by an onboard receiving antenna, in the path of which a polarizing modulator is inserted. A rotating section of a circular waveguide with a quarter-wave phase plate embedded inside is used as a polarizing modulator. The bearing and roll of the aircraft are estimated at the output of a single-channel receiver from amplitudes and phases of the second and fourth harmonics of the polarization modulation frequency, respectively, contained in the envelope spectrum of the received resultant vector signals. [ABSTRACT FROM AUTHOR]

The recent emergence of satellite detection and imaging technologies has increased the demand for the application of satellite cloud images to current weather forecasting. However, approaches based on nonlinear prediction technology to forecast satellite images are lacking, and forecasting timelines are relatively short, e.g., 1–3 h in advance. In the present study, a nonlinear dimensionality reduction approach based on Laplacian eigenmaps (LEs) was combined with a random forest (RF) algorithm to construct an intelligent computing prediction model for rainstorm satellite images obtained from the first annual rainy season (April–June) in South China from 2010 to 2018. Results showed that the proposed forecasting model based on nonlinear intelligent calculation can accurately predict the key features and trends of the development and movement of strong precipitation clouds. The predicted satellite images described by the model were also consistent with the major features of the observed satellite images. This study then used a multiple linear regression (MLR) method based on the same prediction factors to establish a model for predicting satellite images for the same modeling and forecasting samples. Comparative results of the two prediction schemes showed that the LE + RF algorithm satellite image prediction scheme yields more samples exhibiting a high correlation with observed satellite images than the MLR method. Compared with that of the proposed scheme, the amount of samples of the MLR scheme in the low-correlation area was significantly larger. In general, the nonlinear intelligent computing scheme developed in this study is superior to the MLR method for predicting satellite cloud images. Thus, the LE + RF algorithm satellite image prediction scheme provides an objective and practical method for observed satellite cloud image predictions. [ABSTRACT FROM AUTHOR]

Saliency or the salient region changes in the human vision system depending on the type of its behavior and task. That is, the salient region in human vision system is not independent, but dependent on other parameters. If a saliency detection algorithm intends to work like the human vision system, it must have an input as its vision in order to detect that salient region or salient object according to that input. The proposed algorithm of this article (Salient Object Detection using Task Simulation based on Angle) is indeed the updated version of SOD-TS algorithm. In this method we have tried to simulate the task as an angle parameter in order to be able to detect the object independent of its size and rotation. In our proposed method, the algorithm detects the most salient object with regard to the applied task. This method can be used in detecting salient objects, detecting different types of ships, and different types of airplanes, and in edge detection. One of the most important advantages of this approach is its very high speed. [ABSTRACT FROM AUTHOR]

In the western margin of the Ulleung Basin, a detailed analysis of cores with geophysical data from a fan-shaped body, just downslope of a submarine gully associated upslope with failure scars, reveals various modes of mass-transport processes. The arcuate failure scars occurs in water depths exceeding 600 m. The fan-shaped body, less than ca. 10 km long in radius, displays strong backscatter intensity in sonar images, and corresponds to the uppermost transparent mass in Chirp sub-bottom profiles. Sediment cores penetrating to the uppermost transparent mass consist mostly of various facies of mass-transport deposits (MTDs), causing the strong back-intensity in the sonar images. The interval of MTD facies comprises the upper and lower units without hemi-pelagic muds between them, implying that the fan-shaped body was probably deposited during a single event separated in at least two stages without a significant time break. The lower unit shows brittle to plastic deformation of soft muds (slides/slumps), whereas the upper units exhibits fully fragmented soft mud clasts (low viscous debris flows). Both the upper and lower units involve same original lithology (i.e., soft hemi-pelagic mud) prior to failures, suggesting that the lithology could not significantly affect depositional processes. The fully fragmented soft mud clasts of the upper unit are probably indicative of more shearing than the brittle to plastic deformation of soft muds in the lower unit. Considering the small dimension of the failure scars/gully and the same original lithology, the more shearing of the upper unit was most likely caused by longer transport distance than that of the lower unit. The rare turbidites with absence of channellevee systems in the fan-shaped body and the failure scars confined in the upper to middle slopes suggest that the submarine gully probably formed by slope failures, not by erosion of turbidity currents. [ABSTRACT FROM AUTHOR]

In this work, one 8-shaped metasurface (MS) is proposed, which consists of a square array of 8-shaped conducting patches printed on a grounded dielectric substrate and covered by a top dielectric layer. Because the MS is symmetric with respect to both the x- and y-axes, and the phase difference between the reflection coefficients rxx and ryy is close to + 90° in an ultra-wide frequency band, it can be used as an ultra-wideband linear-to-circular polarization converter. Simulation results show that the MS can realize high-efficiency and ultra-wideband linear-to-circular polarization conversion under both u- and v-polarized incidences; the axial ratio (AR) of the reflected wave is below 3 dB in the ultra-wide frequency band of 6.45–24.20 GHz, which is corresponding to a relative bandwidth of 116%; in addition, the polarization conversion rate (PCR) can be maintained larger than 99.5% in the frequency range of 6.78–23.70 GHz, which occupies 95.3% of the 3 dB-axial-ratio-band. Finally, an experimental verification is carried out, a good agreement between the experimental and simulation results is observed. [ABSTRACT FROM AUTHOR]

We investigate electron transport along the surface of WTe2 three-dimensional single crystals, which are characterized by the coexistence of the conductivity and ferroelectricity of a Weyl semimetal at room temperature. We find that a nonlinear behavior of the differential resistance of WTe2 is accompanied by a slow relaxation process, which appears as the dependence on the sign of the current change. This observation is confirmed by direct investigation of time-dependent relaxation curves. While strongly nonlinear differential resistance should be expected for zero-gap WTe2, the slow relaxation in transport is very unusual for well-conducting semimetals at room temperature. We establish that a nonmonotonic dependence of the amplitude of the effect on the driving current well corresponds to the known Sawyer–Tower's ferroelectric hysteresis loop. The possibility to induce polarization current by source-drain field variation is unique for WTe2, since it is a direct consequence of the coexistence of ferroelectricity and metallic conduction. This conclusion is also confirmed by gate voltage dependencies, so our results can be understood as a direct demonstration of the ferroelectric behavior of WTe2 in charge transport experiment. [ABSTRACT FROM AUTHOR]

A novel terahertz metamaterial absorber design with broadband and polarization insensitive absorption characteristics is presented in this paper. This proposed unit cell structure consists of a single layer dielectric with a petal-shaped metallic patch on the top plane. It is found that the absorber offers a broadband absorption of more than 90% over a frequency ranging from 2.6 to 3.5 THz. The absorption mechanism, electric field distribution and parametric analysis for the observed broadband response are also investigated in this paper. The strong coupling effect in the petal-shaped structure contributes to the broadening of the absorption spectrum. Thus, the proposed single-layer absorber can have effective application in terahertz broadband applications. [ABSTRACT FROM AUTHOR]

Early and accurate diagnosis is a critical first step in mitigating losses caused by plant diseases. An incorrect diagnosis can lead to improper management decisions, such as selection of the wrong chemical application that could potentially result in further reduced crop health and yield. In tomato, initial disease symptoms may be similar even if caused by different pathogens, for example early lesions of target spot (TS) caused by the fungus Corynespora cassicola and bacterial spot (BS) caused by Xanthomonas perforans. In this study, hyperspectral imaging (380–1020 nm) was utilized in laboratory and field (collected by an unmanned aerial vehicle; UAV) settings to detect both diseases. Tomato leaves were classified into four categories: healthy, asymptomatic, early and late disease development stages. Thirty-five spectral vegetation indices (VIs) were calculated to select an optimum set of indices for disease detection and identification. Two classification methods were utilized: (i) multilayer perceptron neural network (MLP), and (ii) stepwise discriminant analysis (STDA). Best wavebands selection was considered in blue (408–420 nm), red (630–650 nm) and red edge (730–750 nm). The most significant VIs that could distinguish between healthy leaves and diseased leaves were the photochemical reflectance index (PRI) for both diseases, the normalized difference vegetation index (NDVI850) for BS in all stages, and the triangular vegetation index (TVI), NDVI850 and chlorophyll index green (Chl green) for TS asymptomatic, TS early and TS late disease stage respectively. The MLP classification method had an accuracy of 99%, for both BS and TS, under field (UAV-based) and laboratory conditions. [ABSTRACT FROM AUTHOR]

This article presents the results of experimental studies of properties that are resistant to abnormal high and abnormally low temperatures of samples of the radio-absorbing material VTMV-1C. Based on the studies, it was concluded that the radar-absorbing material can be used to attenuate reflected waves of electromagnetic fields from various parts of the spacecraft structure and to reduce the levels of resonance phenomena of the electromagnetic field in the modules and cases of onboard instruments and devices of spacecraft. [ABSTRACT FROM AUTHOR]