Search

Current signal processing for synthetic aperture radar (SAR) cannot satisfy the requirements for high resolution, high squint angle, and wide swath due to the limitations of the traditional stop-and-go model. This model does not take into account the continuous motion between the satellite and the ground, leading to incomplete compensation for the corresponding phase. To address this issue, we first introduce an accurate range equation (ARE) based on the continuous satellite and ground motion, which allows for more precise slant range calculations. Second, we derive the point target spectrum according to the ARE, revealing additional phase components not considered in the traditional stop-and-go model. Third, we propose an advanced two-step processing algorithm to compensate for phase errors due to nonstop-and-go continuous motion. In the first-step processing, we eliminate range-independent components in the two-dimensional frequency domain. In the second-step processing, we compensate for residual phase errors related to range and azimuth frequency in the range-Doppler domain. We verified the proposed compensation method through simulation and compared it with the two-step compensation method used in high-resolution SAR data processing. Experimental results show that we provide an effective compensation method for high-resolution, high-squint-angle, wide-swath spaceborne SAR, which can correct azimuth shifts and solve the problem of defocusing at the edges of large scenes.

Alveolar bone resorption caused by bacteria‐induced periodontitis remains challenging due to sustained inflammation. Periodontal pathogens like Porphyromonas gingivalis launch the primed signal of NOD‐like receptor family pyrin domain‐containing 3 (NLRP3) inflammasome in macrophages; consequent overproduction of proinflammatory cytokines and reactive oxygen species (ROS) leads to tissue destruction. This provides potential targets for a new therapeutic strategy. Herein, a multifunctionalized and dual‐crosslinked hydrogel pGM/cPL@NI with NLRP3 inhibitor MCC950 loaded is prepared. Driven by the strategic functionalization of gelatin methacryloyl and ε‐poly‐lysine with phenylboronic acid and catechol, respectively, pGM/cPL@NI containing dynamic and photo‐crosslinking networks demonstrates superior mechanical strength and stimuli‐responsive behavior, as well as the overwhelmed performance in bacteria killing and ROS scavenging. Crucially, pGM/cPL@NI restores the compromised osteogenesis by specifically suppressing the proinflammatory cytokine cascade triggered by NLRP3 inflammasome activation and promoting anti‐inflammatory polarization of macrophages. Collectively, pGM/cPL@NI presents robust potential as an effective “cocktail therapy” by combining antibacterial, antioxidant, inflammation resolution, and tissue regenerative functions. The present study reveals the underlying mechanism of the bacterial‐immune‐regeneration cascade and provides an extended approach for periodontal tissue engineering.

The risk of spread of antibiotic-resistant bacteria leads to the growth of implant-associated infection, necessitating the large-scale fabrication of antibacterial materials. The successfully synthetic superhydrophobic and bactericidal materials without durable surfaces are easy to destroy and so difficult to use in a large-scale production in terms of manufacturing costs in performing experiments and processes. In this work, two kinds of microfeatured sieves dipped with high length-diameter ratio silicon carbide whiskers (SiCw) are used as templates for the fabrication of micropillared polypropylene (PP) surfaces embedded with nanospiked SiCw exposed in different postures of standing via a simple low-cost micro-compression molding method. The standing SiCw nanospikes endow the micropillared PP surfaces with a high contact angle (CA) of 153.9° decreased by less than 8° after a wear distance of 1500 mm, exhibiting robust antiwetting and antifriction properties. Further, the nanospiked micropillared PP surfaces exhibit extremely low adhesion and moderate antibacterial efficacy. The micro-/nanoconstructed PP surfaces is expected to approach towards large-scale industrial production for biomedical applications.

Ship detection finds extensive applications in fisheries management, maritime rescue, and surveillance. However, detecting nearshore targets in SAR images is challenging due to land scattering interference and non-axisymmetric ship shapes. Existing SAR ship detection models struggle to adapt to oriented ship detection in complex nearshore environments. To address this, we propose an oriented-reppoints target detection scheme guided by scattering points in SAR images. Our method deeply integrates SAR image target scattering characteristics and designs an adaptive sample selection scheme guided by target scattering points. This incorporates scattering position features into the sample quality measurement scheme, providing the network with a higher-quality set of proposed reppoints. We also introduce a novel supervised guidance paradigm that uses target scattering points to guide the initialization of reppoints, mitigating the influence of land scattering interference on the initial reppoints quality. This achieves adaptive feature learning, enhancing the quality of the initial reppoints set and the performance of object detection. Our method has been extensively tested on the SSDD and HRSID datasets, where we achieved mAP scores of 89.8% and 80.8%, respectively. These scores represent significant improvements over the baseline methods, demonstrating the effectiveness and robustness of our approach. Additionally, our method exhibits strong anti-interference capabilities in nearshore detection and has achieved state-of-the-art performance.

Synthetic Aperture Radar (SAR) images are widely utilized in the field of remote sensing. However, there is a limited body of literature specifically addressing the compression of SAR learning images. To address the escalating volume of SAR image data for storage and transmission, which necessitates more effective compression algorithms, this paper proposes a novel framework for compressing SAR images. Experimental validation is performed using a representative low-resolution Sentinel-1 dataset and the high-resolution QiLu-1 dataset. Initially, we introduce a novel two-stage transformation-based approach aimed at suppressing the low-frequency components of the input data, thereby achieving a high information entropy and minimizing quantization losses. Subsequently, a quality map guidance image compression algorithm is introduced, involving the fusion of the input SAR images with a target-aware map. This fusion involves convolutional transformations to generate a compact latent representation, effectively exploring redundancies between focused and non-focused areas. To assess the algorithm’s performance, experiments are carried out on both the low-resolution Sentinel-1 dataset and the high-resolution QiLu-1 dataset. The results indicate that the low-frequency suppression algorithm significantly outperforms traditional processing algorithms by 3–8 dB when quantifying the input data, effectively preserving image features and improving image performance metrics. Furthermore, the quality map guidance image compression algorithm demonstrates a superior performance compared to the baseline model.

High resolution remains a primary goal in the advancement of synthetic aperture radar (SAR) technology. The backprojection (BP) algorithm, which does not introduce any approximation throughout the imaging process, is broadly applicable and effectively meets the demands for high-resolution imaging. Nonetheless, the BP algorithm necessitates substantial interpolation during point-by-point processing, and the precision and effectiveness of current interpolation methods limit the imaging performance of the BP algorithm. This paper proposes a TSU-ICSI (Time-shift Upsampling-Improved Cubic Spline Interpolation) interpolation method that integrates time-shift upsampling with improved cubic spline interpolation. This method is applied to the BP algorithm and presents an efficient implementation method in conjunction with the GPU architecture. TSU-ICSI not only maintains the accuracy of BP imaging processing but also significantly boosts performance. The effectiveness of the BP algorithm based on TSU-ICSI is confirmed through simulation experiments and by processing measured data collected from both airborne SAR and spaceborne SAR.

The Geosynchronous Satellite Synthetic Aperture Radar (GEO SAR) operates at a high orbital altitude, resulting in an extended imaging time and substantial variations in slant range. Additionally, the GEO SAR satellite orbit experiences a bending effect, and the target’s movement, caused by the Earth’s rotation, is influenced by the Earth’s curvature. The back-projection (BP) algorithm has been proven to be a highly effective technique for precise imaging with GEO SAR by processing these specific echo signals. However, this approach necessitates considerable computational resources. Existing BP algorithms, such as the fast BP algorithm, do not consider the “Stop-and-Go” error present in GEO SAR. Consequently, we developed a Precise Slant Range Model that considers the motion of both the satellite and targets. The model incorporates velocity and acceleration factors to accurately represent the signal transmission from transmission to reception. Additionally, we propose a Rapid Range History Construction Method to lessen the computational burden of generating the three-dimensional range history array. By utilizing the Precise Slant Range Model and the Rapid Range History Construction Method, and employing parallel processing through aperture segmentation, we propose an Accurate and Efficient BP imaging algorithm suitable for GEO SAR applications. To validate its effectiveness, simulations were conducted using the parameters of a GEO SAR system. The results indicated that the proposed algorithm enhances the imaging quality of GEO SAR, reduces the processing time, and achieves high-precision rapid imaging, thereby improving operational efficiency.

To a certain extent, SAR images are affected by range ambiguity due to antenna sidelobe characteristics and pulse operating system. The work of range ambiguity suppression focuses on SAR system design and signal processing. One type of idea tries to modify the way of transmitting and receiving to block the receiving of the ambiguous energy, such as multiple elevation beams and azimuth phase coding. The other ideas are algorithms that use signal processing technology to reduce the distance ambiguity energy in echo and image domains. This paper proposes a range ambiguity suppression method that combines sparse reconstruction and matched filtering. The method performs the sparse reconstruction of the ambiguity area, estimates the ambiguity area signal using the ambiguity area image and reconstruction matrix, separates it from the echo signal to obtain the primary image signal after range ambiguity suppression, and uses matched filtering to obtain the main area image. In this method, sparse reconstruction ensures the accuracy of fuzzy signal estimation, and matched filtering ensures the efficiency of imaging processing. Simulation results show that the proposed method can effectively suppress range ambiguity, with a suppression effect of 10 dB or higher, and it has a good ability to maintain the weak targets and the details of the main image.

In SAR defocused ship images, the defocusing phenomenon of some ship targets is space-variant along the distance. In this context, a novel autofocus algorithm combining the adaptive momentum estimation optimizer and space-variant minimum entropy criteria is proposed to address these defocused ship targets. The algorithm can directly process complex images and compensate for any order phase errors. The effectiveness of the proposed method is proved by the experimental results on the simulation data and GF-3 data. Moreover, the entropy and contrast of the refocused image have been improved, and the focusing speed of the algorithm has been greatly enhanced.

An innovative approach, mainly featured by progressive iteration of partitioning and focusing, to processing very-high-resolution spaceborne synthetic aperture radar (SAR) data is presented in this article. Due to the long integration time endured during data acquisition as well as large scene extensions being common to the advanced SAR systems, spatial dependence of range histories may be severe and must be properly dealt with. In this article, after deriving the exact two dimensional spectrum for an curved satellite orbit, we focus the entire echo data through several iterations of partitioning and focusing. By partitioning, each partitioned data block can be better focused by the following focusing step, and meanwhile, focusing with better quality enables the following partitioning with both higher granularity and less overlapped data region. Besides, a new technique aiming at eliminating spatial dependence inside a data block is also presented and deployed in the processing procedure. Owing to the feature of high granularity partitioning, the spatial dependence of many factors can be accommodated finer and easier compared with other conventional algorithms. What is more, the artifacts caused by subaperture recombination are fundamentally avoided by the fact that the partitioned blocks are not recombined until being processed into fully focused image blocks. Finally, the precision and the efficiency of the proposed methodology are validated by results on a simulated and a real SAR data.

Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) has been extensively applied in military and civilian fields. However, SAR images are very sensitive to the azimuth of the images, as the same target can differ greatly from different aspects. This means that more reliable and robust multiaspect ATR recognition is required. In this paper, we propose a multiaspect ATR model based on EfficientNet and BiGRU. To train this model, we use island loss, which is more suitable for SAR ATR. Experimental results have revealed that our proposed method can achieve 100% accuracy for 10-class recognition on the Moving and Stationary Target Acquisition and Recognition (MSTAR) database. The SAR targets in three special imaging cases with large depression angles, version variants, and configuration variants reached recognition accuracies of 99.68%, 99.95%, and 99.91%, respectively. In addition, the proposed method achieves satisfactory accuracy even with smaller datasets. Our experimental results show that our proposed method outperforms other state-of-the-art ATR methods on most MSTAR datasets and exhibits a certain degree of robustness.

Bacteria in nature are present in different lifestyles with distinct characteristics. Streptococcus mutans is the etiologic pathogen of dental caries and could easily gain access into the bloodstream after oral surgery and adopt a biofilm lifestyle, resulting in infective endocarditis. A growing amount of evidence have revealed that the large web-like structure composed of extracellular DNA and antimicrobial proteins released by neutrophils, named Neutrophil Extracellular Traps (NETs), play an active role in the defense against bacterial invasion. The present study demonstrated that NETs formation was discriminatively affected by S. mutans biofilm and its planktonic counterpart. The free-floating planktonic S. mutans exhibited an active NETs response, whereas the biofilm community exhibited a reverse negative NETs response. Besides, impaired biofilm killing correlated with the decrease in NETs production. Unlike planktonic cells, biofilm avoided the burst of reactive oxygen species (ROS) when co-culture with neutrophils, and the NADPH-oxidase pathway was partially involved. A mice infection model also supported the distinguishing response of neutrophils challenged by different lifestyles of S. mutans. In conclusion, different bacterial physiological states can affect the distinct response of the host–microbe interaction, thus contributing to the anti-pathogen immune response activation and immune surveillance survival.

Ground-based radar has been used for Moon imaging for more than 60 years. Five-hundred-meter Aperture Spherical radio Telescope (FAST), as the largest radio telescope on Earth, holds significant potential for celestial imaging missions with its exceptional sensitivity. A bistatic Synthetic Aperture Radar (SAR) Moon imaging model that incorporates FAST and other transmitting radars is presented. The objective of this paper is to design the imaging parameters of this bistatic configuration based on the required resolution, and to estimate the resolution performance based on a given bistatic system capability. Considering the ultra-far range and the ultra-long observation time between the radars and the Moon, the geometric relationship involved in this bistatic configuration is significantly distinct from the bistatic configuration of airborne and spaceborne radars. Therefore, this paper accurately derives the two-dimensional resolution on the Moon’s surface. First of all, the models of the Earth’s surface and the Moon’s surface, and the celestial motion of the Earth and Moon are established using WGS-84 and JPL-DE421, given by STK. Secondly, the bistatic range history within the observation time is calculated in terms of continuous celestial motion instead of the popular ‘stop-and-go’ assumption. Thirdly, no approximation is used in the resolution derivation process, and, in addition to the two-dimensional resolutions, the incident angle and the included angle are also given to describe the imaging performance. This method can also be extended to other bistatic-station and single-station celestial imaging, providing support for radar location and parameters design, for observation time span selection, for observation area selection, and for imaging performance estimation. The echo generation and imaging for point targets set on the Moon are shown. The simulation results prove the validity and accuracy of the proposed method in the paper.

Airborne Synthetic Aperture Radar (SAR) location error is affected by the position/speed measurement error of the aircraft, system time error, etc., and also related to the residual error of motion compensation. However, the existing airborne SAR location model rarely considers the effect of residual motion error. Considering that motion and trajectory measurement errors are common in practice, this paper derives a location error transfer model of an airborne SAR image based on the motion compensation and frequency-domain imaging algorithms. The proposed model clarifies the influence of trajectory measurement error on location deviation when residual motion error exists and provides a method of error calibration measurement. The simulation experiments validate the correctness of the proposed location error transfer model. The present method obtains a more accurate error calibration measurement result than the location error model that does not consider the residual motion error, proving the superiority of the proposed model.

Summary: Genome-wide sequencing (GWS) is a standard of care for diagnosis of suspected genetic disorders, but the proportion of patients found to have pathogenic or likely pathogenic variants ranges from less than 30% to more than 60% in reported studies. It has been suggested that the diagnostic rate can be improved by interpreting genomic variants in the context of each affected individual’s full clinical picture and by regular follow-up and reinterpretation of GWS laboratory results.Trio exome sequencing was performed in 415 families and trio genome sequencing in 85 families in the CAUSES study. The variants observed were interpreted by a multidisciplinary team including laboratory geneticists, bioinformaticians, clinical geneticists, genetic counselors, pediatric subspecialists, and the referring physician, and independently by a clinical laboratory using standard American College of Medical Genetics and Genomics (ACMG) criteria. Individuals were followed for an average of 5.1 years after testing, with clinical reassessment and reinterpretation of the GWS results as necessary. The multidisciplinary team established a diagnosis of genetic disease in 43.0% of the families at the time of initial GWS interpretation, and longitudinal follow-up and reinterpretation of GWS results produced new diagnoses in 17.2% of families whose initial GWS interpretation was uninformative or uncertain. Reinterpretation also resulted in rescinding a diagnosis in four families (1.9%). Of the families studied, 33.6% had ACMG pathogenic or likely pathogenic variants related to the clinical indication. Close collaboration among clinical geneticists, genetic counselors, laboratory geneticists, bioinformaticians, and individuals’ primary physicians, with ongoing follow-up, reanalysis, and reinterpretation over time, can improve the clinical value of GWS.

Oral health is crucial to daily life, yet many people worldwide suffer from oral diseases. With the development of oral tissue engineering, there is a growing demand for dental biomaterials. Addressing oral diseases often requires a two-fold approach: fighting bacterial infections and promoting tissue growth. Hydrogels are promising tissue engineering biomaterials that show great potential for oral tissue regeneration and drug delivery. In this review, we present a classification of hydrogels commonly used in dental research, including natural and synthetic hydrogels. Furthermore, recent applications of these hydrogels in endodontic restorations, periodontal tissues, mandibular and oral soft tissue restorations, and related clinical studies are also discussed, including various antimicrobial and tissue growth promotion strategies used in the dental applications of hydrogels. While hydrogels have been increasingly studied in oral tissue engineering, there are still some challenges that need to be addressed for satisfactory clinical outcomes. This paper summarizes the current issues in the abovementioned application areas and discusses possible future developments.

A large amount of cyanide-containing wastewater is discharged during electrode material synthesis. Among them, cyanides will form metal–cyanide complex ions which possess high stability, making it challenging to separate them from these wastewaters. Therefore, it is imperative to understand the complexation mechanism of cyanide ions and heavy metal ions from wastewater in order to obtain a deep insight into the process of cyanide removal. This study employs Density Functional Theory (DFT) calculations to reveal the complexation mechanism of metal–cyanide complex ions formed by the interaction of Cu+ and CN− in copper cyanide systems and its transformation patterns. Quantum chemical calculations show that the precipitation properties of Cu(CN)43− can assist in the removal of CN−. Therefore, transferring other metal–cyanide complex ions to Cu(CN)43− can achieve deep removal. OLI studio 11.0 analyzed the optimal process parameters of Cu(CN)43− under different conditions and determined the optimal process parameters of the removal depth of CN−. This work has the potential to contribute to the future preparation of related materials such as CN− removal adsorbents and catalysts and provide theoretical foundations for the development of more efficient, stable, and environmentally friendly next-generation energy storage electrode materials.

Human dentin, as an important calcified tissue in the body, plays significant roles in withstanding masticatory forces and has a complex hierarchical organization. Understanding the composition and ultrastructure of dentin is critical for elucidating mechanisms of biomineralization under healthy and pathological states. Here, atomic force microscope infrared spectroscopy (AFM-IR) and AFM-based amplitude modulation-frequency modulation (AM-FM) techniques were utilized to detect the heterogeneity in chemical composition and mechanical properties between peritubular and intertubular dentin at the nanoscale. AFM-IR spectra collected from peritubular and intertubular dentin contained similar vibrational bands in the amide regions (I, II and III), suggesting that collagen may exist in both structures. A distinctive band at 1336 cm−1 indicative of SO stretching vibrations was detected only in peritubular dentin. AFM-IR imaging showed an uneven distribution of chemical components at different locations, confirming the heterogeneity of dentin. The Young’s modulus of peritubular dentin was higher, and was associated to a higher mineral content. This study demonstrated distinctive chemical and mechanical properties of peritubular dentin, implying the different development and mineralization processes between peritubular and intertubular dentin. AFM-IR is useful to provide compositional information on the heterogeneity of human dentin, helping to understand the mineral deposition mechanisms of dentin. Keywords: Infrared spectroscopy, Human dentin, Atomic force microscopy, Amplitude modulation, Frequency modulation, Young’s modulus

The theoretical modeling and analysis of synthetic aperture radar (SAR) location error play an important role in SAR system design and error source budget. The existing SAR geolocation error models are mainly implicit, which are not easy to do analysis, especially in the curved-path case. In this paper, a theoretical explicit model of the relationship between image geolocation error and the path measurement error is established for curved-path SAR, based on back projection imaging algorithm. The simulations of multiple sets of parameters verify the correctness of the proposed model. The explicit model and the analysis results provide an effective reference for understanding and budgeting the system-level geometric location error for curved-path SAR, such as geosynchronous orbit synthetic aperture radar.

The Geosynchronous Synthetic Aperture Radar (GEO SAR) has a long synthetic aperture time. The temporal decoherence and azimuth variance characteristics of echo are significant, that brings great challenges to signal to process. In order to reduce the synthetic aperture time and thus improve the observation flexibility and efficiency, this paper proposes a SAR system mounted on a special satellite in reverse equatorial geosynchronous orbit, so-called the reverse equatorial GEO SAR. The orbit is nearly circular and the orbital plane coincides with the equatorial plane. The satellite flies against the direction of the Earth's rotation. The relative velocity is accelerated twice and the synthetic aperture time is shorter. The satellite does not drift in latitude direction and drifts uniformly in longitude direction. The echo has azimuth invariance property. Meanwhile, the 24-hour continuous observation can be achieved for areas with a certain range of latitude by means of large squint technique and constellation design. As the GEO SAR has high orbit, large delay, large squint angle, and wide pulse width, the complex modulation effects are generated by continuous motion between the satellite and target during the imaging period. In this paper, the uniform acceleration curve motion is used to describe the motion of both satellite and target, and the linear approximation is used to describe the slant range change in the process of transmitting and receiving one pulse. Accordingly, an accurate signal model for the reverse equatorial GEO SAR is established, which provides a theoretical model for signal characteristics analysis and imaging algorithms development.

Previous ground-based, radar lunar imaging experiments have usually employed the Range-Doppler (RD) algorithm. This algorithm performs in the frequency domain and has high computational efficiency. However, in the case of a long coherent integration time, the defocus phenomenon will appear, and the image will be smeared. This study proposes the use of the back projection (BP) algorithm to obtain focused lunar images to solve this problem. The BP algorithm is a time-domain algorithm which is frequently employed in synthetic aperture radar (SAR) imaging and can theoretically achieve the focused imaging of each pixel in an arbitrarily long coherent integration time. However, the largest drawback of this algorithm is its high computational complexity. Therefore, this study only applies this method to map local regions of the moon. We select Sanya incoherent scatter radar (SYISR) as the transmitting and receiving device and utilize the linear frequency modulation chirp pulse to transmit right-hand, circularly polarized electromagnetic waves and to receive left-hand, circularly polarized echoes. RD and BP algorithms are simultaneously adopted to image the Pythagoras crater region, and a contrastive analysis is performed. The results show that the BP algorithm can be well applied to a ground-based, radar lunar imaging experiment and that it has a better focusing performance, but the effect is not as obvious as expected. Thus, the processing method needs to be further improved. In addition, the computational efficiency of BP is very low, and certain fast algorithms need to be applied to improve it.

Periodontitis, a common disease that can lead to bone destruction, periodontal attachment loss, and tooth loss, is the major cause for oral tissue engineering. Experimental periodontitis is a suitable disease-model for studying bone regeneration and the potential therapeutic role of biomaterials on periodontal tissue engineering, as this in vivo model could be employed to mimic the natural host response under bacteria-caused oral pathological environments. Although large animals with ligature-induced periodontitis have mostly been used for experiments, a mouse model is a better choice for several reasons. Inserting ligature threads through the interproximal space between the teeth is the key step in establishing a periodontitis model, and it is easy to achieve in large animals, but difficult in mice due to the limited operating space. In this work, we provide a new and proven approach for periodontitis induction in mice using C+ nickel-titanium root canal files and stainless-steel ligature wires. The validity of this method was assessed by evaluating alveolar bone loss via micro-CT and detecting periodontal inflammation by histological staining and qPCR after the treatments. Progressive alveolar bone loss was observed from day 3 after the ligature-placement. Infiltration and accumulation of F4/80+ macrophage was also detected. In accordance with the histological results, there was upregulation of the expression levels of the inflammatory genes Il1β, Tnf-α, and Il6 in gingival tissues isolated from the ligation sites. Our results suggest that this novel method could resolve the difficulty of ligature-placement in mice and consequently contribute to further use of mouse models for studying the pathological mechanisms of periodontitis and developing potential periodontal tissue regeneration strategies. C+ files, which are made of nickel-titanium, are tough, elastic, and sufficiently thin to pass through the interproximal space between the teeth after pre-bending to form an appropriate angle, thus providing an access for ligature wire insertion. As a common tool in the dental clinic, it is familiar to researchers of oral biology, and can provide the feasibility for wide application of our method.

The phenotypic spectrum associated with the skeletal muscle voltage-gated sodium channel gene (SCN4A) has expanded with advancements in genetic testing. Autosomal dominant SCN4A mutations were first linked to hyperkalemic periodic paralysis, then subsequently included paramyotonia congenita, several variants of myotonia, and finally hypokalemic periodic paralysis. Biallelic recessive mutations were later identified in myasthenic myopathy and in infants showing a severe congenital myopathy with hypotonia. We report a patient with a pathogenic de novo SCN4A variant, c.2386C>G p.L796V at a highly conserved leucine. The phenotype was manifest at birth with arthrogryposis multiplex congenita, severe episodes of bronchospasm that responded immediately to carbamazepine therapy, and electromyographic evidence of widespread myotonia. Another de novo case of p.L796V has been reported with hip dysplasia, scoliosis, myopathy, and later paramyotonia. Expression studies of L796V mutant channels showed predominantly gain-of-function changes, that included defects of slow inactivation. Computer simulations of muscle excitability reveal a strong predisposition to myotonia with exceptionally prolonged bursts of discharges, when the L796V defects are included. We propose L796V is a pathogenic variant, that along with other cases in the literature, defines a new dominant SCN4A disorder of myotonic myopathy with secondary congenital joint and skeletal involvement.

Abstract Background Hypertrophic cardiomyopathy (HCM) is characterized by left ventricular hypertrophy (LVH) in the absence of predisposing cardiovascular conditions. Pathogenic variants in at least 16 cardiac sarcomeric genes have been implicated in HCM, most of which act in a dominant‐negative fashion. However loss‐of‐function (haploinsufficiency) is the most common disease mechanism for pathogenic variants in MYBPC3, suggesting that MYBPC3 complete deletion may play a role in HCM pathogenesis. Here, we investigate MYBPC3 complete deletion as a disease mechanism in HCM by analyzing two unrelated patients with confirmed diagnosis of HCM that tested negative by Sanger sequencing analysis. Methods MYBPC3 complete deletion was investigated by Multiplex ligation‐dependent probe amplification (MLPA) and microarray analyses. The mechanism of deletion was investigated by interrogating the SINEBase database. Results Patient‐1 was diagnosed with nonobstructive HCM in his mid‐40s while undergoing assessment for palpitations, and patient‐2 with obstructive HCM in his late‐20s while undergoing systolic heart murmur assessment for an unrelated illness. MLPA testing revealed a heterozygous deletion of all MYBPC3 exons in both patients. Subsequent microarray testing confirmed these deletions which extended beyond the 5′ and 3′ ends of MYBPC3. Genomic assessment suggested that these deletions resulted from Alu/Alu‐homologous recombination. Conclusion Our results demonstrate that haploinsufficiency resulting from MYBPC3 complete deletion, potentially mediated by Alu recombination, is an important disease mechanism in cardiomyopathy and emphasizes the importance of copy number variation analysis in patients clinically suspected of HCM.

At present, synthetic aperture radar (SAR) automatic target recognition (ATR) has been deeply researched and widely used in military and civilian fields. SAR images are very sensitive to the azimuth aspect of the imaging geomety; the same target at different aspects differs greatly. Thus, the multi-aspect SAR image sequence contains more information for classification and recognition, which requires the reliable and robust multi-aspect target recognition method. Nowadays, SAR target recognition methods are mostly based on deep learning. However, the SAR dataset is usually expensive to obtain, especially for a certain target. It is difficult to obtain enough samples for deep learning model training. This paper proposes a multi-aspect SAR target recognition method based on a prototypical network. Furthermore, methods such as multi-task learning and multi-level feature fusion are also introduced to enhance the recognition accuracy under the case of a small number of training samples. The experiments by using the MSTAR dataset have proven that the recognition accuracy of our method can be close to the accruacy level by all samples and our method can be applied to other feather extraction models to deal with small sample learning problems.

This paper focuses on an improved imaging algorithm for spotlight synthetic aperture radar (SAR) with continuous Pulse Repetition Interval (PRI) variation in extremely high-resolution. Conventional SAR systems are limited in that a wide swath cannot be achieved with a high azimuth resolution in the meantime. This limitation can be overcome by Pulse Repetition Frequency (PRF) variation in a SAR system. However, there are problems such as the ambiguities of point targets or extended targets caused by nonuniform sampling. A reconstructive method, Nonuniform Discrete Fourier Transform (NUDFT) has been presented in the current literature, but it is rather computationally expensive. In this paper, a modified sinc interpolation based on NUDFT is proposed, which is used to reconstruct the uniformly sampled echo in time domain. Since the interpolation kernel length is relatively short, it is more computationally efficient. Then, the two-step processing approach combined with the modified sinc interpolation is further presented, which has much better accuracy than that combined with the conventional sinc interpolation. Both the simulated data and the extracted GF-3 data experiment demonstrate the validity and accuracy of the proposed approach.

When the original echo data of SAR are saturated for quantization, the performance of the commonly used block adaptive quantization (BAQ) algorithm will be degraded, which will degrade the imaging quality. This article proposes an improved Llody-Max codec method, which only needs to change the codec look-up table to get better quantization performance when the original echo is saturated. The simulation results show that the proposed method can reduce the quantization power loss, improve the echo signal-to-noise ratio (SNR), and reduce the influence of quantization saturation on the scattering mechanism of polarized SAR data, which have good practical application value.