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Synthetic Aperture Radar (SAR) ship detection is crucial for maritime surveillance, environmental monitoring, and national security. Recently, methods based on deep learning have been successfully applied to ship detection for SAR images. Despite the development of numerous ship detection methodologies, detecting small and coastal ships remains a significant challenge due to the limited features and clutter in coastal environments. For that, a novel adaptive multi-hierarchical attention module (AMAM) is proposed to learn multi-scale features and adaptively aggregate salient features from various feature layers, even in complex environments. Specifically, we first fuse information from adjacent feature layers to enhance the detection of smaller targets, thereby achieving multi-scale feature enhancement. Then, to filter out the adverse effects of complex backgrounds, we dissect the previously fused multi-level features on the channel, individually excavate the salient regions, and adaptively amalgamate features originating from different channels. Thirdly, we present a novel adaptive multi-hierarchical attention network (AMANet) by embedding the AMAM between the backbone and the feature pyramid network (FPN). Besides, the AMAM can be readily inserted between different frameworks to improve object detection. Lastly, extensive experiments on two large-scale SAR ship detection datasets, namely the SSDD and HRSID, demonstrate that our AMANet method achieves superior performance over state-of-the-art methods, with an AP of 74.20% and 68.90% on the SSDD and HRSID datasets, respectively.

Bisecting N-acetylglucosamine (GlcNAc), a GlcNAc linked to the core β-mannose residue via a β1,4 linkage, is a special type of N-glycosylation that has been reported to be involved in various biological processes, such as cell adhesion and fetal development. This N-glycan structure is abundant in human trophoblasts, which is postulated to be resistant to natural killer cell-mediated cytotoxicity, enabling a mother to nourish a fetus without rejection. In this study, we hypothesized that the human amniotic membrane, which serves as the last barrier for the fetus, may also express bisected-type glycans. To test this hypothesis, glycomic analysis of the human amniotic membrane was performed, and bisected N-glycans were detected. Furthermore, our proteomic data, which have been previously employed to explore human missing proteins, were analyzed and the presence of bisecting GlcNAc-modified peptides was confirmed. A total of 41 glycoproteins with 43 glycopeptides were found to possess a bisecting GlcNAc, and 25 of these glycoproteins were reported to exhibit this type of modification for the first time. These results provide insights into the potential roles of bisecting GlcNAc modification in the human amniotic membrane, and can be beneficial to functional studies on glycoproteins with bisecting GlcNAc modifications and functional studies on immune suppression in human placenta.

This paper focuses on the finite-time (FNT) cluster synchronization issues for a class of delayed fractional-order fully complex-valued community networks (FFCVCNs). A new mathematical expression of the complex networks is developed with internal delay, non-delayed and delayed couplings, complex-valued state variables, system function, coupling strengths, inner coupling matrices and outer coupling matrices. Instead of transforming the complex-valued (CV) networks into two independent real-valued (RV) systems, the delay-dependent controllers are designed based on the quadratic norm and a novel norm composed of the absolute-valued norm to realize the cluster synchronization for the proposed complex networks in FNT, respectively. In addition, the upper bounds of the settling time (ST) when the system could reach finite-time cluster synchronization are estimated. The obtained results are less conservative than some of the existing studies due to the characteristics of fully fractional-order complex-valued (FOCV) dynamical networks. The feasibility and effectiveness of the main results are demonstrated by simulation examples.

Infrared and visible image fusion combine data information from different sensors to achieve a richer description of the same scene. In order to highlight the salient features of the infrared image and the visible image in the fusion image and obtain a fusion image with good performance, an end-to-end infrared and visible image fusion algorithm is proposed in this paper. The contrast attention module and visible image cascade part are introduced in the generator, so that the fusion image can focus on the detail information in the visible image and the contrast information in the infrared image. And in order to retain more structural contour information in the original image, the contour loss is added to the content loss function. In addition, the contrast and detail information in infrared and visible images are balanced by two discriminators. And a goal-guided reward function is introduced into the discriminator, which further facilitates the generator to produce effective fused images. Finally, extensive fusion experiments on public datasets verify the advantages of the proposed algorithm compared with other classical algorithms, and ablation experiments demonstrate the effectiveness of the improved part of the algorithm.

Abstract Although there are various Conus species with publicly available transcriptome and proteome data, no genome assembly has been reported yet. Here, using Chinese tubular cone snail (C. betulinus) as a representative, we sequenced and assembled the first Conus genome with original identification of 133 genome-widely distributed conopeptide genes. After integration of our genomics, transcriptomics, and peptidomics data in the same species, we established a primary genetic central dogma of diverse conopeptides, assuming a rough number ratio of ~1:1:1:10s for the total genes: transcripts: proteins: post-translationally modified peptides. This ratio may be special for this worm-hunting Conus species, due to the high diversity of various Conus genomes and the big number ranges of conopeptide genes, transcripts, and peptides in previous reports of diverse Conus species. Only a fraction (45.9%) of the identified conotopeptide genes from our achieved genome assembly are transcribed with transcriptomic evidence, and few genes individually correspond to multiple transcripts possibly due to intraspecies or mutation-based variances. Variable peptide processing at the proteomic level, generating a big diversity of venom conopeptides with alternative cleavage sites, post-translational modifications, and N-/C-terminal truncations, may explain how the 133 genes and ~123 transcripts can generate thousands of conopeptides in the venom of individual C. betulinus. We also predicted many conopeptides with high stereostructural similarities to the putative analgesic ω-MVIIA, addiction therapy AuIB and insecticide ImI, suggesting that our current genome assembly for C. betulinus is a valuable genetic resource for high-throughput prediction and development of potential pharmaceuticals.

Image fusion technology can process multiple single image data into more reliable and comprehensive data, which play a key role in accurate target recognition and subsequent image processing. In view of the incomplete image decomposition, redundant extraction of infrared image energy information and incomplete feature extraction of visible images by existing algorithms, a fusion algorithm for infrared and visible image based on three-scale decomposition and ResNet feature transfer is proposed. Compared with the existing image decomposition methods, the three-scale decomposition method is used to finely layer the source image through two decompositions. Then, an optimized WLS method is designed to fuse the energy layer, which fully considers the infrared energy information and visible detail information. In addition, a ResNet-feature transfer method is designed for detail layer fusion, which can extract detailed information such as deeper contour structures. Finally, the structural layers are fused by weighted average strategy. Experimental results show that the proposed algorithm performs well in both visual effects and quantitative evaluation results compared with the five methods.

Scorpion venom is deemed to contain many toxic peptides as an important source of natural compounds. Out of the two hundred proteins identified in Mesobuthus martensii (M. martensii), only a few peptide toxins have been found so far. Herein, a combinational approach based upon RNA sequencing and Liquid chromatography-mass spectrometry/mass spectrometry (LC MS/MS) was employed to explore the venom peptides in M. martensii. A total of 153 proteins were identified from the scorpion venom, 26 previously known and 127 newly identified. Of the novel toxins, 97 proteins exhibited sequence similarities to known toxins, and 30 were never reported. Combining peptidomic and transcriptomic analyses, the peptide sequence of BmKKx1 was reannotated and four disulfide bridges were confirmed within it. In light of the comparison of conservation and variety of toxin amino acid sequences, highly conserved and variable regions were perceived in 24 toxins that were parts of two sodium channel and two potassium channel toxins families. Taking all of this evidences together, the peptidomic analysis on M. martensii indeed identified numerous novel scorpion peptides, expanded our knowledge towards the venom diversity, and afforded a set of pharmaceutical candidates.

Rationale High specificity of trypsin is a prerequisite for accurate identification and quantification of proteins in shotgun proteomics. It is important to minimize nonspecific enzymatic cleavages during proteomic sample preparation. Methods: In this study, protein extraction and trypsin digestion conditions were extensively evaluated using the less-complex Escherichia coli lysates to improve the sensitivity of detecting low-abundance nonspecific peptides by liquid chromatography/tandem mass spectrometry. Results: Trypsin digestion buffers and digestion times were proved to have a significant effect on nonspecific cleavages. The triethylammonium bicarbonate buffer induces significantly lower nonspecific cleavages than the other two buffers, but a freshly prepared urea solution does not induce more than sodium dodecyl sulfate. Because prolonged trypsin digestion resulted in a considerable number of nonspecific cleavages, an optimized 2-h protocol was developed with 45.2% less semispecific tryptic peptides but 18.5% more unmodified peptides identified than the commonly used 16-h protocol. Conclusions: The significant decrease in nonspecific cleavages and artificial modifications improves the accuracy of protein quantification and the identification of low-abundance proteins, and it is especially useful for studying protein posttranslational modifications. For trypsin digestion, the proposed 2-h protocol can potentially be a replacement for the traditional 16-h protocol. [ABSTRACT FROM AUTHOR]

Background: The venom of predatory marine cone snails mainlycontainsadiversearrayofuniquebioactive peptides commonly referred to as conopeptides or conotoxins. These peptides have proven to be valuable pharmacological probes and potential drugs because of their high specificity and affinity to important ion channels, receptors and transporters of the nervous system. Most previous studies have focused specifically on the conopeptides from piscivorous and molluscivorous cone snails, but little attention has been devoted to the dominant vermivorous species. Results: The vermivorous Chinese tubular cone snail, Conus betulinus, is the dominant Conus species inhabiting the South China Sea. The transcriptomes of venom ducts and venom bulbs from a variety of specimens of this species were sequenced using both next-generation sequencing and traditional Sanger sequencing technologies, resulting in the identification of a total of 215 distinct conopeptides. Among these, 183 were novel conopeptides, including nine new superfamilies. It appeared that most of the identified conopeptides were synthesized in the venom duct, while a handful of conopeptides were identified only in the venom bulb and at very low levels. Conclusions: We identified 215 unique putative conopeptide transcripts from the combination of five transcriptomes and one EST sequencing dataset. Variation in conopeptides from different specimens of C. betulinus was observed, which suggested the presence of intraspecific variability in toxin production at the genetic level. These novel conopeptides provide a potentially fertile resource for the development of new pharmaceuticals, and a pathway for the discovery of new conotoxins. [ABSTRACT FROM AUTHOR]

Fish venom remains a virtually untapped resource. There are so few fish toxin sequences for reference, which increases the difficulty to study toxins from venomous fish and to develop efficient and fast methods to dig out toxin genes or proteins. Here, we utilized Chinese yellow catfish (Pelteobagrus fulvidraco) as our research object, since it is a representative species in Siluriformes with its venom glands embedded in the pectoral and dorsal fins. In this study, we set up an in-house toxin database and a novel toxin-discovering protocol to dig out precise toxin genes by combination of transcriptomic and proteomic sequencing. Finally, we obtained 15 putative toxin proteins distributed in five groups, namely Veficolin, Ink toxin, Adamalysin, Za2G and CRISP toxin. It seems that we have developed a novel bioinformatics method, through which we could identify toxin proteins with high confidence. Meanwhile, these toxins can also be useful for comparative studies in other fish and development of potential drugs. [ABSTRACT FROM AUTHOR]

Shaking is one of the key processes contributing to the quality formation of oolong tea. As an abiotic stress factor, mechanical stress leads to a series of physiological and biochemical changes in plants through various biological effects, which has been widely used in the processing of scented black tea, scented white tea, scented green tea and other tea types to improve their quality. In order to ascertain the physiological changes of green tea leaves in response to mechanical stress, postharvest fresh shoots with 3–4 leaves?from the tea cultivar ‘Tieguanyin’ were evaluated for changes in water content, photosystem II (PS II) parameters, antioxidant enzyme activities and subcellular structure under natural spreading or continuous vibration stress treatment after withering. Compared with naturally spread leaves and withered leaves, the water content in the leaves subjected to vibration stress was not significantly different within the first 30 min of vibration (P > 0.05) but was significantly lower at 60 min (P < 0.05). The green-grassy odor became stronger with increasing vibration time, the refreshing aroma became weaker, and the clear compact lamellar structures of the chloroplast and the thylakoid were gradually loosened, deformed, shrunk, and disrupted. The number of starch granules increased significantly at 5 min, and the number of osmiophilic granules increased significantly at 15 min, resulting in the formation of aggregates. The actual photosynthetic efficiency Y (II) and photochemical quenching coefficient (qP) of PS II generally showed a decreasing trend with increasing vibration time, and the electron transfer rate (ETR) declined initially and then rose. The Y (II) and ETR at 5 and 10 min of vibration were significantly lower than those observed in naturally spread leaves (P < 0.05). The quantum yield Y (NO) of non-regulated energy dissipation increased with the prolongation of vibration stress treatment time, and was significantly higher than that of naturally spread leaves at 30 min (P < 0.05). The relative conductivity of tea leaves under vibration stress for 10 min was significantly higher than that of naturally spread leaves (P < 0.05). The activities of ascorbate peroxidase, dehydroascorbate reductase and glutathione reductase in tea leaves under vibration stress for 5 and 10 min were higher than those in naturally spread leaves. Vibration treatment (for up to 30 min) did not show significant variations in water content, but enhanced the green-grassy odor. Continuous vibration treatment caused cell injuries by increasing the cell membrane permeability, thereby facilitating the release of intracellular contents and increasing cell conductivity. At the subcellular level, vibration treatment promoted thylakoid degradation and severely damaged chloroplasts, thus destroying PS II stability. Meanwhile, it protected tea leaf cells against mechanical stress-induced damage by elevating the activities of defense enzymes. Taken together, this study lays a foundation for the regulating of shaking during the processing of oolong tea.