An Efficient ΣΔ-STAP Detector for Radar Seeker using RPCA Post-processing

Adaptive detection of moving targets in sea clutter environment is considered as one of the crucial tasks for radar seekers. Due to the severe spreading of the sea clutter spectrum, the ability of space-time adaptive processing with sum and difference beams (ΣΔ-STAP) algorithms to suppress the sea clutter is very limited. This paper, investigated the low-rank property of the range-Doppler data matrix according to the eigenvalue distribution from the eigen spectrum, and proposed an efficient ΣΔ-STAP detector based on the robust principle component analysis (RPCA) algorithm to detect moving targets, which meets the low-rank matrix recovery conditions. The proposed algorithm first adopts ΣΔ-STAP algorithm to preprocess the sea clutter, then separates the sparse matrix of target component from the range-Doppler data matrix through the RPCA algorithm, and finally, effectively detects moving targets in the range-Doppler plane. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm in the low signal-to-noise ratio scenarios.Defence Science Journal, Vol. 64, No. 4, July 2014, pp. 344-349, DOI:http://dx.doi.org/10.14429/dsj.64.486

Label-free microfluidic paper-based electrochemical aptasensor for ultrasensitive and simultaneous multiplexed detection of cancer biomarkers

Simultaneous detection of multiple tumor biomarkers in body fluids could facilitate early diagnosis of lung cancer, so as to provide scientific reference for clinical treatment. This paper depicted a multi-parameter paper-based electrochemical aptasensor for simultaneous detection of carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) in a clinical sample with high sensitivity and specificity. The paper-based device was fabricated through wax printing and screen-printing, which enabled functions of sample filtration and sample auto injection. Amino functional graphene (NG)-Thionin (THI)- gold nanoparticles (AuNPs) and Prussian blue (PB)- poly (3,4- ethylenedioxythiophene) (PEDOT)- AuNPs nanocomposites were synthesized respectively. They were used to modify the working electrodes not only for promoting the electron transfer rate, but also for immobilization of the CEA and NSE aptamers. A label-free electrochemical method was adopted, enabling a rapid simple point-of-care testing. Experimental results showed that the proposed multi-parameter aptasensor exhibited good linearity in ranges of 0.01-500 ng mL for CEA (R  = 0.989) and 0.05-500 ng mL for NSE (R  = 0.944), respectively. The limit of detection (LOD) was 2 pg mL for CEA and 10 pg mL for NSE. In addition, the device was evaluated using clinical serum samples and received a good correlation with large electrochemical luminescence (ECL) equipment, which would offer a new platform for early cancer diagnostics, especially in those resource-limit areas

Exploring Reinforced Class Separability and Discriminative Representations for SAR Target Open Set Recognition

Current synthetic aperture radar (SAR) automatic target recognition (ATR) algorithms primarily operate under the closed-set assumption, implying that all target classes have been previously learned during the training phase. However, in open scenarios, they may encounter target classes absent from the training set, thereby necessitating an open set recognition (OSR) challenge for SAR-ATR. The crux of OSR lies in establishing distinct decision boundaries between known and unknown classes to mitigate confusion among different classes. To address this issue, we introduce a novel framework termed reinforced class separability for SAR target open set recognition (RCS-OSR), which focuses on optimizing prototype distribution and enhancing the discriminability of features. First, to capture discriminative features, a cross-modal causal features enhancement module (CMCFE) is proposed to strengthen the expression of causal regions. Subsequently, regularized intra-class compactness loss (RIC-Loss) and intra-class relationship aware consistency loss (IRC-Loss) are devised to optimize the embedding space. In conjunction with joint supervised training using cross-entropy loss, RCS-OSR can effectively reduce empirical classification risk and open space risk simultaneously. Moreover, a class-aware OSR classifier with adaptive thresholding is designed to leverage the differences between different classes. Consequently, our method can construct distinct decision boundaries between known and unknown classes to simultaneously classify known classes and identify unknown classes in open scenarios. Extensive experiments conducted on the MSTAR dataset demonstrate the effectiveness and superiority of our method in various OSR tasks

On the Catalytic Activity of Sn Monomers and Dimers at Graphene Edges and the Synchronized Edge Dependence of Diffusing Atoms in Sn Dimers

In this study, in situ transmission electron microscopy is performed to study the interaction between single (monomer) and paired (dimer) Sn atoms at graphene edges. The results reveal that a single Sn atom can catalyze both the growth and etching of graphene by the addition and removal of C atoms respectively. Additionally, the frequencies of the energetically favorable configurations of an Sn atom at a graphene edge, calculated using density functional theory calculations, are compared with experimental observations and are found to be in good agreement. The remarkable dynamic processes of binary atoms (dimers) are also investigated and is the first such study to the best of the knowledge. Dimer diffusion along the graphene edges depends on the graphene edge termination. Atom pairs (dimers) involving an armchair configuration tend to diffuse with a synchronized shuffling (step-wise shift) action, while dimer diffusion at zigzag edge terminations show a strong propensity to collapse the dimer with each atom diffusing in opposite directions (monomer formation). Moreover, the data reveals the role of C feedstock availability on the choice a single Sn atom makes in terms of graphene growth or etching. This study advances the understanding single atom catalytic activity at graphene edges. © 2021 The Authors. Advanced Functional Materials published by Wiley-VCH Gmb

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Anchored Single-atom catalysts have emerged as a cutting-edge research field holding tremendous appeal for applications in the fields of chemicals, energy and the environment. However, single-atom-catalysts for crystal growth is a nascent field. Of the few studies available, all of them are based on state-of-the-art in situ microscopy investigations and computational studies, and they all look at the growth of monolayer graphene from a single-atom catalyst. Despite the limited number of studies, they do, collectively, represent a new sub-field of single-atom catalysis, namely single-atom catalytic growth of crystalline solids. In this review, we examine them on substrate-supported and as freestanding graphene fabrication, as well as rolled-up graphene, viz., single-walled carbon nanotubes (SWCNT), grown from a single atom. We also briefly discuss the catalytic etching of graphene and SWCNT’s and conclude by outlining the future directions we envision this nascent field to take

Harmonic-seeded remote laser emissions in N2-Ar, N2-Xe and N2-Ne mixtures: a comparative study

We report on the investigation on harmonic-seeded remote laser emissions at 391 nm wavelength from strong-field ionized nitrogen molecules in three different gas mixtures, i.e., N2-Ar, N2-Xe and N2-Ne. We observed a decrease in the remote laser intensity in the N2-Xe mixture because of the decreased clamped intensity in the filament; whereas in the N2-Ne mixture, the remote laser intensity slightly increases because of the increased clamped intensity within the filament. Remarkably, although the clamped intensity in the filament remains nearly unchanged in the N2-Ar mixture because of the similar ionization potentials of N2 and Ar, a significant enhancement of the lasing emission is realized in the N2-Ar mixture. The enhancement is attributed to the stronger third harmonic seed, and longer gain medium due to the extended filament.Comment: 10 pages, 5 figure

Autophagy regulates the maturation of hematopoietic precursors in the embryo

An understanding of the mechanisms regulating embryonic hematopoietic stem cell (HSC) development would facilitate their regeneration. The aorta-gonad-mesonephros region is the site for HSC production from hemogenic endothelial cells (HEC). While several distinct regulators are involved in this process, it is not yet known whether macroautophagy (autophagy) plays a role in hematopoiesis in the pre-liver stage. Here, we show that different states of autophagy exist in hematopoietic precursors and correlate with hematopoietic potential based on the LC3-RFP-EGFP mouse model. Deficiency of autophagy-related gene 5 (Atg5) specifically in endothelial cells disrupts endothelial to hematopoietic transition (EHT), by blocking the autophagic process. Using combined approaches, including single-cell RNA-sequencing (scRNA-seq), we have confirmed that Atg5 deletion interrupts developmental temporal order of EHT to further affect the pre-HSC I maturation, and that autophagy influences hemogenic potential of HEC and the formation of pre-HSC I likely via the nucleolin pathway. These findings demonstrate a role for autophagy in the formation/maturation of hematopoietic precursors.</p