MCML-BF: A Metal-Column Embedded Microstrip Line Transmission Structure with Bias Feeders for Beam-Scanning Leakage Antenna Design.

This article proposes a novel fixed-frequency beam scanning leakage antenna based on a liquid crystal metamaterial (LCM) and adopting a metal column embedded microstrip line (MCML) transmission structure. Based on the microstrip line (ML) transmission structure, it was observed that by adding two rows of metal columns in the dielectric substrate, electromagnetic waves can be more effectively transmitted to reduce dissipation, and attenuation loss can be lowered to improve energy radiation efficiency. This antenna couples TEM mode electromagnetic waves into free space by periodically arranging 72 complementary split ring resonators (CSRRs). The LC layer is encapsulated in the transmission medium between the ML and the metal grounding plate. The simulation results show that the antenna can achieve a 106° continuous beam turning from reverse -52° to forward 54° at a frequency of 38 GHz with the holographic principle. In practical applications, beam scanning is achieved by applying a DC bias voltage to the LC layer to adjust the LC dielectric constant. We designed a sector-blocking bias feeder structure to minimize the impact of RF signals on the DC source and avoid the effect of DC bias on antenna radiation. Further comparative experiments revealed that the bias feeder can significantly diminish the influence between the two sources, thereby reducing the impact of bias voltage introduced by LC layer feeding on antenna performance. Compared with existing approaches, the antenna array simultaneously combines the advantages of high frequency band, high gain, wide beam scanning range, and low loss.

Extended-depth-of-field imaging with an ultra-thin folded lens.

Optical systems with extended depth of field (EDOF) are crucial for observation and measurement applications, where achieving compactness and a substantial depth of field (DOF) presents a considerable challenge with conventional optical elements. In this paper, we propose an innovative solution for the miniaturization of EDOF imaging systems by introducing an ultra-thin annular folded lens (AFL). To validate the practical feasibility of the theory, we design an annular four-folded lens with an effective focal length of 80.91 mm and a total thickness of only 8.50 mm. Simulation results show that the proposed folded lens has a DOF of 380.55 m. We further developed an AFL-based test system exhibiting a resolution of 0.11 mrad across a wide wavelength range of 486-656 nm. Additionally, we present experimental results from a miniature compact prototype, which further highlights the promising potential of folded lenses for long-range EDOF imaging.

Investigation of the Multimechanism Laser Cleaning Dynamics for Rough Fused Silica Surfaces with Organic Contaminants: A Computational Simulation and Atomic Analysis.

The detrimental impact of organic contaminants on optical components poses a significant obstacle to high-energy laser systems. However, irregularities or defects on the surface of optical components during manufacturing can affect the process of organic contaminant removal. Thus, a comprehensive understanding of the intricate interplay among surface roughness, contaminant absorption, and ablation is essential to effectively address the challenges of laser-induced damage. In this study, a molecular dynamics approach was employed to investigate the interaction between laser-fused silica and contaminants and to analyze the influence of surface roughness on the removal of contaminants from fused silica. Research findings demonstrate that during laser irradiation, organic contaminants on the surface of mechanical components diffuse into the optical elements. As the laser flux increases, the contaminants gradually decompose into smaller molecular clusters. Additionally, the phenomenon of contaminant ablation is observed to consist of two distinct phases: the "Thermal expansion phase" and the "Thermal ablation phase." The study examines the impact of substrate roughness on the contaminant removal in these two phases. It is found that a higher surface roughness leads to stronger thermal expansion and vaporization of contaminants. With increasing roughness of the fused silica substrate, the corresponding van der Waals energy and pressure decrease under the same laser fluence, making the removal of contaminants easier. These results provide valuable insights into the interaction between laser irradiation and organic contaminants.

An Infrared Small Target Detection Method Based on Attention Mechanism.

The human visual attention system plays an important role in infrared target recognition because it can quickly and accurately recognize infrared small targets and has good scene adaptability. This paper proposes an infrared small target detection method based on an attention mechanism, which consists of three modules: a bottom-up passive attention module, a top-down active attention module, and decision feedback equalization. In the top-down active attention module, given the Gaussian characteristics of infrared small targets, the idea of combining knowledge-experience Gaussian shape features is applied to implement feature extraction, and quaternion cosine transform is performed to achieve multi-dimensional fusion of Gaussian shape features, thereby achieving complementary fusion of multi-dimensional feature information. In the bottom-up passive attention module, considering that the difference in contrast and motion between the target and the background can attract attention easily, an optimal fast local contrast algorithm and improved circular pipeline filtering are adopted to find candidate target regions. Meanwhile, the multi-scale Laplacian of the Gaussian filter is adopted to estimate the optimal size of the infrared small target. The fast local contrast algorithm based on box filter acceleration and structure optimization is employed to extract local contrast features, and candidate target regions can be obtained by using an adaptive threshold. Besides, the mean gray, target size, Gaussian consistency, and circular region constraint are used in pipeline filtering to extract motion regions, and the false-alarm rate is reduced effectively. Finally, decision feedback equalization is adopted to obtain real targets. Experiments are conducted on some real infrared images involving complex backgrounds with sea, sky, and ground clutters, and the experimental results indicate that the proposed method can achieve better detection performance than conventional baseline methods, such as RLCM, ILCM, PQFT, MPCM, and ADMD. Also, mathematical proofs are provided to validate the proposed method.

Optofluidic zoom system with increased field of view and less chromatic aberration.

Imaging systems are widely used in many fields. However, there is an inherent compromise between field of view (FOV) and resolution. In this paper, we propose an optofluidic zoom system with increased FOV and less chromatic aberration, which can realize switching between large FOV and high resolution. The proposed system consists of a liquid prism, a zoom objective, an image sensor and image processing module, which can realize optical zoom and deflection. The proposed system achieves non-mechanical optical zoom from f = 40.5 mm to f = 84.0 mm. Besides, the angular resolution of zoom objective is up to 26"18 at f = 84.0 mm. The deflection range is ±10°, and the whole FOV of proposed system can reach up to 30.3°. The proposed system is compact and easy to machine. In addition, we reduce chromatic aberration produced by the liquid prism significantly. The proposed system can be used in monitor system, target tracking system, telescope system and so on.

Multi-domain-fusion deep learning for automatic modulation recognition in spatial cognitive radio.

Automatic modulation recognition (AMR) is a critical technology in spatial cognitive radio (SCR), and building high-performance AMR model can achieve high classification accuracy of signals. AMR is a classification problem essentially, and deep learning has achieved excellent performance in various classification tasks. In recent years, joint recognition of multiple networks has become increasingly popular. In complex wireless environments, there are multiple signal types and diversity of characteristics between different signals. Also, the existence of multiple interference in wireless environment makes the signal characteristics more complex. It is difficult for a single network to accurately extract the unique features of all signals and achieve accurate classification. So, this article proposes a time-frequency domain joint recognition model that combines two deep learning networks (DLNs), to achieve higher accuracy AMR. A DLN named MCLDNN (multi-channel convolutional long short-term deep neural network) is trained on samples composed of in-phase and quadrature component (IQ) signals, to distinguish modulation modes that are relatively easy to identify. This paper proposes a BiGRU3 (three-layer bidirectional gated recurrent unit) network based on FFT as the second DLN. For signals with significant similarity in the time domain and significant differences in the frequency domain that are difficult to distinguish by the former DLN, such as AM-DSB and WBFM, FFT (Fast Fourier Transform) is used to obtain frequency domain amplitude and phase (FDAP) information. Experiments have shown that the BiGUR3 network has superior extraction performance for amplitude spectrum and phase spectrum features. Experiments are conducted on two publicly available datasets, the RML2016.10a and RML2016.10b, and the results show that the overall recognition accuracy of the proposed joint model reaches 94.94% and 96.69%, respectively. Compared to a single network, the recognition accuracy is significantly improved. At the same time, the recognition accuracy of AM-DSB and WBFM signals has been improved by 17% and 18.2%, respectively.

Influence of reactive oxygen species concentration and ambient temperature on the evolution of chemical bonds during plasma cleaning: a molecular dynamics simulation.

The research on plasma chemistry involved in the formation and dissociation of abundant chemical bonds is fundamental to developing plasma cleaning. To understand the influence of reactive oxygen species' concentration and ambient temperature on the evolution behavior of the chemical bond during plasma cleaning, microscopic reaction models between organic contaminants and reactive oxygen species were established and performed by reactive molecular dynamics. Dibutyl phthalate, as a representative organic contaminant, was selected as the research object. The simulation results suggested that hydrogen bonds between hydroxyl radicals reduced the mobility of reactive species, resulting in the cleaning ability of hydroxyl radicals being much lower than atomic oxygen and ozone radicals. The concentration of reactive species dominated the efficiency of plasma cleaning, and the increase in ambient temperature further improved the cleaning ability. C-H, C-C and C-O bonds were gradually oxidized to C[double bond, length as m-dash]C, C-O, C[double bond, length as m-dash]O and O-H bonds by hydrogen abstraction reaction during the reaction of reactive species with organic contaminants. An increase in ambient temperature induced the possibility of benzene ring destruction under the action of reactive species, which was considered a method of complete dissociation of aromatic hydrocarbons.

Spectral diagnosis of in situ plasma cleaning in large-aperture optical components: reactive species characterization and prediction of cleaning.

The damage of large-aperture optical components caused by organic contamination limits the performance improvement of high-power laser facilities. We propose an in situ plasma cleaning technology to remove the organic contaminants on large-aperture optical components, demonstrated by the simulated equipment. The cleaning characteristics of the equipment were investigated by spectral diagnosis. The cleaning capability coefficient was defined to evaluate the performance of the plasma equipment. Then diffusion properties of reactive species along the surface of optical components were elucidated under various charge parameters, including powers, source frequencies, and gas pressures. We discuss the underlying cleaning mechanism for removing organic contaminants. A new plasma cleaning model is established to predict the treatment time with the cleaning capability coefficient.

Anesthetic effect of ultrasound-guided multiple-nerve blockade in modified radical mastectomy in patients with breast cancer.

INTRODUCTION: Routine anesthesia modality for modified radical mastectomy (MRM) includes general anesthesia (GA), epidural blockade-combined GA and nerve blockade-combined GA. However, GA has been associated with postoperative adverse effects such as vertigo, postoperative nausea and vomiting and requirement for postoperative analgesia, which hinders recovery and prognosis. Moreover, combined blockade of thoracic paravertebral nerves or intercostal nerves and adjuvant basic sedation for massive lumpectomy provided perfect anesthesia and reduced opioid consumption, whereas the excision coverage did not attain the target of MRM. Regional anesthesia strategies involving supplementation of analgesics in ultrasound-guided multiple nerve blocks have garnered interests of clinicians. Nevertheless, the precise effects of intercostal nerves, brachial plexus and supraclavicular nerves in MRM in patients with breast cancer remain obscure. METHODS: Eighty female patients with breast cancer scheduled for MRM were recruited in the present trial between May, 2019 and Dec., 2019 in our hospital. The patients ranged from 30 to 65 years of age and 18∼30 kg/m2 in body-mass index, with the American Society of Anesthesiologists I or II. The patients were randomized to ultrasound-guided multiple nerve blocks group and GA group. The patients in multiple nerve blocks group underwent ultrasound guided multiple intercostal nerve blocks, interscalene brachial plexus and supraclavicular nerve blocks, (local anesthesia with 0.3% ropivacaine: 5 ml for each intercostal nerve block, 8 ml for brachial plexus block, 7 mL for supraclavicular nerve block) and basic sedation and intraoperative mask oxygen inhalation. The variations of hemodynamic parameters such as mean arterial pressure, heart rate (HR) and pulse oxygen saturation were monitored. The visual analog scale scores were recorded at postoperative 0 hour, 3 hour, 6 hour, 12 hour and 24 hour in resting state. The postoperative adverse effects, including vertigo, postoperative nausea, and vomiting, pruritus, and urinary retention and so on, as well as the analgesic consumption were recorded. CONCLUSIONS: The ultrasound guided multiple intercostal nerve blocks, brachial plexus and supraclavicular nerve blocks could provide favorable anesthesia and analgesia, with noninferiority to GA and the reduced incidence of adverse effects and consumption of postoperative analgesics.

Photodetectors Based on Micro-nano Structure Material.

Photodetectors converting optical signals into electrical signals have been widely utilized and have received more and more attention in scientific research and industrial fields including optical interconnection, optical communication, and environmental monitoring. Herein, we summarize the latest development of photodetectors with different micro-nano structures and different materials and the performance indicators of photodetectors. Several photodetectors, such as flexible, ultraviolet two-dimensional (2D) microscale, and dual-band photodetectors, are listed in this minireview. Meanwhile, the current bottleneck and future development prospects of the photodetector are discussed.

Facile fabrication of the zoledronate-incorporated coating on magnesium alloy for orthopaedic implants.

BACKGROUND: Bisphosphonates (BPs) are known as a group of well-established drugs which are clinically used in metabolic bone disorder-related therapies. Recently increasing interests are focused on the application of BPs in the biodegradable Mg-based implants. METHODS: In this study a facile method was applied to fabricate a zoledronate loaded coating on AZ31 Mg alloy in comparison with the previous construction strategies, such as Ca-P chelation with BPs. RESULTS: The results showed that the fluoride pretreated coating could provide better corrosion resistance. Zoledronic acid (ZA) was successfully loaded on the surface of Mg alloy detected by X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) analysis, and the release profile was quantified with Ultraviolet (UV) detection. CONCLUSION: It is considered that this construction of ZA coated Mg-based orthopedic implants could be easily and efficiently used in clinic. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: Different from the traditional drug release mode, this paper used the hydrogen bond between drug molecules and drug carriers to not only realise the effective drug release in the early stage of drug release, but also meet the continuous effect of drugs in the later stage, providing a new possibility for clinical application.

P-S-N Curve Description of Laser Metal Deposition Ti-6.5Al-2Zr-1Mo-1V Titanium Alloy after Duplex Annealing.

Fatigue tests were conducted on standard smooth laser metal deposition (LMD) Ti-6.5Al-2Zr-1Mo-1V titanium alloy specimens under three constant-amplitude stresses. The mixed failure behaviors and the influence of internal pores on the fatigue life were discussed in detail. The double-peak characteristics of the fatigue life distribution have been observed, and a bimodal lognormal distribution (BLG) with five variables can be used to describe the fatigue life variation. A parameter estimation method based on the maximum likelihood estimation (MLE) method was proposed to estimate the BLG distribution parameters, and the Newton⁻Raphson algorithm was used to solve the nonlinear equations derived from the likelihood functions. A P-S-N curve description of LMD titanium alloy was established based on the BLG and verified by fatigue life data obtained from a fatigue test.