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High‐resolution interference pattern images are vital for spatial heterodyne Raman spectroscopy to produce quality Raman spectra with a good signal‐to‐noise ratio. A sought‐after super‐resolution algorithm can enhance Raman interference pattern images, reducing reliance on expensive imaging sensors. This enables miniaturization and portability for point‐of‐care testing. This study proposes a generative adversarial network (GAN)‐based super‐resolution reconstruction algorithm explicitly designed for Raman interference patterns. Employing GAN adversarial training, the algorithm effectively reconstructs interference pattern images at higher resolution, improving Raman spectra signal‐to‐noise ratio. Considering Raman spectra analysis mainly focuses on characteristic peaks, a Raman characteristic peak‐focused network training scheme is used. For instance, acetaminophen is studied with two selected Raman characteristic peaks centered at 388 and 858 cm−1. These peaks are observed in Fourier transformed Raman spectra from corresponding low‐resolution interference pattern images obtained by down‐sampling high‐resolution ones by twofold and fourfold. The proposed GAN‐based algorithm successfully reconstructs low‐resolution interference patterns into high‐resolution ones, achieving high R‐square values (96.05% for twofold and 91.1% for fourfold). This innovation holds potential for point‐of‐care applications, like noninvasive blood glucose concentration measurements, enabling cost‐effective, portable Raman spectrometers with improved capabilities. [ABSTRACT FROM AUTHOR]

In this article, we present a broadband metamaterial absorber (MA) designed for planar microwave circuits, which focuses on the absorption of an electromagnetic wave (EMW) that flows parallel to the direction of the transmission. This MA consists of complementary double‐split rectangles (CDSRs) with a dielectric layer on top of a metallic ground plane, which can be added to a planar microwave circuit as a bottom layer to absorb the EMWs. With further optimization, a composite CDSR‐MA is proposed that operates between 6.5 GHz and 11.2 GHz and covers X‐band communication frequencies. Modeling and simulation is performed using the CST studio software. The absorption bandwidth of this CCDSR‐MA is 6.5‐11.2 GHz, with absorption above 0.75 and the maximum absorption reaches 0.96 at 10.2 GHz. A sample on a five‐layered circuit board using standard print circuit board technology is fabricated to test this CCDSR‐MA, with an outer dimension of 13.4 mm × 137 mm. The simulation and experimental results agree well with each other. [ABSTRACT FROM AUTHOR]

Single-image super-resolution (SISR) techniques have found wide applications in semiconductor defect inspection. Enhancing image resolution to improve inspection sensitivity and accuracy holds great significance. A novel SISR algorithm, called cross-convolutional residual network (CCRN), is proposed in this study. CCRN comprises a cross-convolutional module (CCM), which incorporates a cross-sharing mechanism that facilitates the fusion of features from different stages, enabling the extraction of more information from the image. Moreover, a global residual aggregation structure (GRA) is introduced. GRA captures and transfers different levels of residual features acquired from learning each CCM to the reconstruction layer. Experimental results demonstrate that the proposed SR algorithm outperforms existing state-of-the-art SR algorithms in terms of both visual and quantitative metrics when applied to optical, SEM, and TEM images of microfluidic chips, CMOS image sensors, and quantum dots, respectively. Additionally, CCRN significantly improves the accuracy of defect classification and inspection of unpatterned wafers, as evaluated using the WM-811K dataset. Notably, an increase in local defection testing accuracy from 79.00% to 89.00% and an improvement in classification accuracy from 93.69% to 96.06% are achieved. These findings underscore the potential applications of the proposed algorithm in improving semiconductor defect inspection and classification accuracies. [ABSTRACT FROM AUTHOR]

In this paper, a thermal-insensitive ultra-broadband metamaterial absorber (MMA) based on indium tin oxide (ITO) patterns and the SiO2 dielectric substrate is proposed to demonstrate high-temperature stability and excellent absorbability. The surface patterns consist of two different sizes of rectangular split-ring resonators with two gaps in each split-ring. Results from simulation indicate that at the initial temperature of 300 K, the relative absorption bandwidth reaches 83.35%, and the spectrum with absorptivity higher than 90% ranges from 8.00 GHz to 19.43 GHz. Moreover, in the temperature range of 300–700 K, the effective bands remain steady and cover more than 95% of the initial band. The simulation results also verify that the performance of MMA remains stable when exposed to high-intensity incident and high temperature of 500 K. The analysis of the surface current, electromagnetic (EM) field, power-loss density, equivalent circuit, and constitutive EM parameters reveals the mechanisms of thermal-insensitive ultra-broadband. This study expands potential applications of MMAs in conditions with thermal-stable demands. [ABSTRACT FROM AUTHOR]

A Ka-band, folded waveguide traveling wave tube (FWG-TWT) composed of a folded waveguide (FWG) slow wave structure (SWS) and a compact lumped resistance metamaterial absorber (LR-MMA) as a sever load is proposed in this article. The LR-MMA consists of five resonant rings with a metallic ground plane and a separating silica layer. Lumped resistances are used and concentrated resistances are added at the opening of the resonant ring to match the surface impedance of the LR-MMA with that of the metallic waveguide. Simulation results show that the proposed LR-MMA has an absorption bandwidth of 3 GHz at 34-GHz center frequency with absorption exceeding 90%. A FWG-TWT using this LR-MMA is simulated; the output power of this traveling wave tube (TWT) is 112.5 W at 34 GHz, corresponding to a gain of 51.5 dB. The performance of the FWG-SWS using the LR-MMA is similar to that of the FWG-SWS using a wedge sever (WS). For this FWG-SWS, the sever load length of the proposed metamaterial attenuator (MMA) is 0.5 mm, which is much shorter than 9.4 mm of the traditional WS. The LR-MMA is suitable for microfabrication technology and it can be easily assembled with a FWG-SWS, which is helpful for achieving an integrated SWS for the TWT. [ABSTRACT FROM AUTHOR]

To tackle the issues of high training expense, inadequate real-time functionality, and insufficient reliability in deep neural network-based visual detection of conveyor belt damage, which significantly limit the practical use of the detection model in industrial settings, this study proposes a novel YoloX-ECA damage detection method, based on the YoloX. Initially, the backbone network CSPDarknet is used for feature extraction, followed by invoking channel attention mechanism ECA on the enhance feature extraction network, which fuses multi-scale damage features and further amplifies the attention on damage target feature, facilitating the extraction of superior features to reinforce resistance to environmental interference. Additionally, the training strategy combines cross-domain transfer and intra-domain transfer learning to improve the training performance and robustness of the model. The experimental results demonstrate that YoloX-ECA has a detection accuracy of 95.65% and a speed of 30.50 fps. Moreover, compared to existing methods, the detection performance of the proposed method is effectively upgraded, resulting in a balanced accuracy and rate of conveyor belt damage detection. [ABSTRACT FROM AUTHOR]

Abstract MicroRNA-135a-5p has been reported to play a potential role in the generation of new neurons. However, the underlying targets of miR-135a-5p in regulating neuronal differentiation have been poorly understood. Our study recently has uncovered that Sox6 and CD44 genes were significantly downregulated during neuronal differentiation of P19 cells, a multipotent cell type. We then found that Sox6 directly bound to the promoter of CD44. Importantly, we identified Sox6 as a direct target of miR-135a-5p. Additionally, we demonstrated that miR-135a-5p is crucial for the neuronal differentiation of P19 cells. More significantly, we found that Sox6 overexpression could overturn miR-135a-5p-mediated neuronal differentiation and dendrite development. In conclusion, these findings indicated that miR-135a-5p/Sox6/CD44 axis provides an important molecular target mechanism for neurodifferentiation. Highlights • Sox6 is identified as a suppressor of neuronal differentiation. • Sox6 directly targets CD44. • Sox6 is verified as a direct target of miR-135a-5p. • miR-135a-5p is critical for efficient neuronal differentiation. [ABSTRACT FROM AUTHOR]

Abstract Major depression is a highly prevalent disorder with no effective medical treatments available. Recent evidence has shown that sirtuins (SIRTs) signaling has been implicated to play an essential in the pathogenesis of depression. Here in this study, we aimed to investigate the potential role of the phencynonate hydrochloride (PHH) in rat models of chronic unpredictable mild stress (CUMS)-induced depression. SIRT6 expression was up-regulated by PHH via increasing NAD+/NADH ratio in the prefrontal cortex. PHH was able to suppress CUMS-induced oxidative stress and enhance the antioxidant capacity and antioxidant proteins activity, such as superoxide dismutase 2 (SOD2) and peroxiredoxin 6 (Prdx6). In vitro study, we found that SIRT6 directly bound to SOD2 and Prdx6 and deacetylated them at Lys68/122 and Lys63/209, which were acetylated by p300/CBP-associated factor (PCAF). Finally, we showed that PHH ameliorated CUMS-induced depressive phenotypes by up-regulating SIRT6 deacetylation activity. In summary, PHH -mediating SIRT6 pathway is required for antidepressant response and PHH can be used as a novel therapeutic to effectively treat depression. Highlights • PHH activates SIRT6 expression by increasing NAD+/NADH ratio. • SIRT6 directly deacetylates SOD2 and Prdx6 at Lys68/122 and Lys63/209. • PHH modulates antioxidant capacity by up-regulating SIRT6 deacetylation activity. • PHH may be developed as a therapeutic drug for the treatment of MDD patients. [ABSTRACT FROM AUTHOR]