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Metasurface absorbers have shown significant potential in stealth applications due to their adaptability and capacity to reduce the backscattering of electromagnetic (EM) waves. Nevertheless, due to the materials used in the terahertz (THz) range, simultaneously achieving excellent stealth performance in ultrawideband remains an important and difficult challenge to overcome. In this study, an ultrawideband absorber is proposed based on indium tin oxide (ITO) and polyethylene-terephthalate (PET), with a structure thickness of only 0.16λ. ITO sheets are utilized to achieve broad-spectrum, optical transparency and flexibility of the metasurface. The results show that absorption higher than 90% can be achieved in the frequency band ranging from 1.75 to 5 THz under normal TE and TM polarizations, which covers a wide THz band. The structure is insensitive to polarization angles and exhibits 97% relative bandwidth above 90% efficiency up to an oblique incident angle of 60°. To further validate the efficiency of the absorption performance, the radar cross-section (RCS) reduction investigation was performed on both planar and conformal configurations. The findings show that under normal incidence EM waves, both flat and curved surfaces can achieve RCS reduction of over 10 dB, covering an extremely wide frequency range of 1.75 to 5 THz. The metasurface presented in this study exhibits significant potential for use in several THz applications, including flexible electronic devices and stealth aircraft windows. [ABSTRACT FROM AUTHOR]

Multifunctional integrated meta-devices are the demand of modern communication systems and are given a lot of attention nowadays. Most of the research has focused on either cross-polarization conversion (CPC) or linear-to-circular (LP–CP) conversion. However, simultaneously realizing multiple bands with good conversion efficiency remains crucial. This paper proposes a multiband and multifunctional dual reflective polarization converter surface capable of converting a linearly polarized (LP) wave into a circularly polarized (CP) wave, in frequency bands of 12.29–12.63 GHz, 16.08–24.16 GHz, 27.82–32.21 GHz, 33.75–38.74 GHz, and 39.70–39.79 GHz, with 3 dB axial ratio bandwidths of 2.7%, 40.15%, 14.6%, 13.76%, and 0.2%, respectively. Moreover, the converter is capable of achieving CPC with a polarization conversion ratio (PCR) that exceeds 95%, within the frequency ranges of 13.10–14.72 GHz, 25.43–26.00, 32.46–32.56 GHz, and 39.14–39.59 GHz. In addition, to identify the fundamental cause of the CPC and LP–CP conversion, a comprehensive theoretical investigation is provided. Furthermore, the surface current distribution patterns at different frequencies are investigated to analyze the conversion phenomena. A sample prototype consisting of 20 × 20 unit cells was fabricated and measured, verifying our design and the simulated results. The proposed structure has potential applications in satellite communications, radar, stealth technologies, and reflector antennas. [ABSTRACT FROM AUTHOR]

The diversified ocular disorders in which cystoid macular edema (CME) occurs, are strongly associated with the vision loss. Optical coherence tomography (OCT) scans that allow screening of the retina, contain artifacts including blur‐edges, speckle noise, and so forth, which create difficulty in identifying retinal fluid. In this work, major image preprocessing techniques such as minimum filtering, block‐matching and 3D filtering, and Richardson–Lucy deconvolution method are applied to minimize noise and other degradation effects from OCT scans, ensured by maintaining image quality assessment scores, that is, blind‐less image spatial quality evaluator and sharpness estimation score. Furthermore, this work develops an automated method based on deep learning (DL) to detect the presence and progression of retinal fluid, that is, CME and its quantification. Specifically, U‐net model with efficient tuning of hyperparameters is proposed to obtain optimal results. The algorithm's performance is evaluated for accurate identification of fluid localization in the case of diabetic macular edema (DME), having CME regions, and compared against the manual segmentation of fluid by experts, which are highly correlated. This enhanced DL method achieves better performance than the algorithms previously reported. The proposed algorithm is evaluated on several performance metrics during training and reports the best score of 99.81, 0.50, 83.34, 86.56, 80.89, and 99.48% for model accuracy, binary cross‐entropy loss, Dice coefficient (DC), precision, recall, and area under the ROC‐curve, respectively. Additionally, fourfold cross‐validation technique is also applied and an average DC score of 84.00% is obtained. This approach can be helpful to prevent vision loss. [ABSTRACT FROM AUTHOR]