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Objectives: Rapid antigen test (RAT) and polymerase chain reaction (PCR) using nasopharyngeal (NP) or oropharyngeal (OP) swab specimens are the two main testing techniques used for laboratory diagnosis of influenza in clinical practice. However, performance variations have been observed not only between techniques, but also between different specimens. This study evaluated the differences in performance between specimens and testing techniques to identify the best combination in clinical practice. Methods: Both NP and OP samples from suspected influenza patients collected in the 2023/4–2023/5 Flu-season in Xiamen, China, were tested for RAT and quantitative PCR. The testing performance of the different specimens and testing techniques were recorded and evaluated. Results: Compared to PCR, RAT showed 58.9 % and 10.3 % sensitivity for NP and OP swabs, respectively. The Limit of Detection (LoD) was 28.71 the Median Tissue Culture Infectious Dose (TCID50)/mL. Compared with PCR using NP swabs, PCR with OP swabs showed 89.5 % sensitivity and 95.4 % specificity. Conclusions: There were no significant differences in performance between the specimens when PCR was used to test for influenza. However, a decrease in sensitivity was observed when the RAT was used, regardless of the specimen type. Therefore, to avoid false-negative results, PCR may be a better choice when OP swabs are used as specimens. In contrast, NP swabs should be the recommended specimens for RAT.

Space radiation particle detection plays a crucial role in scientific research and engineering practice, especially in particle species identification. Currently, commonly used in-orbit particle identification techniques include telescope methods, electrostatic analysis time of flight (ESA × TOF), time-of-flight energy (TOF × E), and pulse shape discrimination (PSD). However, these methods usually fail to utilize the full waveform information containing rich features, and their particle identification results may be affected by the random rise and fall of particle deposition and noise interference. In this study, a low-latency and lightweight onboard FPGA real-time particle identification platform based on full waveform information was developed utilizing the superior target classification, robustness, and generalization capabilities of convolutional neural networks (CNNs). The platform constructs diversified input datasets based on the physical features of waveforms and uses Optuna and Pytorch software architectures for model training. The hardware platform is responsible for the real-time inference of waveform data and the dynamic expansion of the dataset. The platform was utilized for deep learning training and the testing of the historical waveform data of neutron and gamma rays, and the inference time of a single waveform takes 4.9 microseconds, with an accuracy rate of over 97%. The classification expectation FOM (figure-of-merit) value of this CNN model is 133, which is better than the traditional pulse shape discrimination (PSD) algorithm’s FOM value of 0.8. The development of this platform not only improves the accuracy and efficiency of space particle discrimination but also provides an advanced tool for future space environment monitoring, which is of great value for engineering applications.

Lithium metal has been treated as one of the most promising anode materials for next-generation rechargeable batteries due to its extremely high theoretical capacity. However, its practical application is hindered by inhomogeneous lithium deposition and uncontrolled dendrite growth. In this work, we prepared a three-dimensional nickel foam (NF)-based current collector with a lithiophilic interface layer through facile hydrothermal and coating methods. The lithiophilic Ni3S2 array synthesized via a hydrothermal method has been demonstrated to facilitate the nucleation of Li+. Moreover, it has been observed that the outer coating comprising LPP effectively enhances the inward diffusion of Li+. Additionally, this interface layer can serve as an isolating barrier between the electrodes and the electrolyte. The prepared LPP-Ni3S2@Ni shows significant reversibility both in symmetric cells (1200 h, 1 mA cm−2) and half-cells (CE: 99.60%, 500 cycles, 1 mA cm−2) with low interfacial resistance (35 Ω). Full cells with LiFePO4 as a cathode also exhibit promising electrochemical performance with over 76.78% capacity retention over 200 cycles at 1 C.

As a low-calorie sugar, D-allulose is produced from D-fructose catalyzed by D-allulose 3-epimerase (DAE). Here, to improve the catalytic activity, stability, and processability of DAE, we reported a novel method by forming organic–inorganic hybrid nanoflowers (NF-DAEs) and co-immobilizing them on resins to form composites (Re-NF-DAEs). NF-DAEs were prepared by combining DAE with metal ions (Co2+, Cu2+, Zn2+, Ca2+, Ni2+, Fe2+, and Fe3+) in PBS buffer, and were analyzed by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy, and X-ray diffraction. All of the NF-DAEs showed higher catalytic activities than free DAE, and the NF-DAE with Ni2+ (NF-DAE-Ni) reached the highest relative activity of 218%. The NF-DAEs improved the thermal stability of DAE, and the longest half-life reached 228 min for NF-DAE-Co compared with 105 min for the free DAE at 55 °C. To further improve the recycling performance of the NF-DAEs in practical applications, we combined resins and NF-DAEs to form Re-NF-DAEs. Resins and NF-DAEs co-effected the performance of the composites, and ReA (LXTE-606 neutral hydrophobic epoxy-based polypropylene macroreticular resins)-based composites (ReA-NF-DAEs) exhibited outstanding relative activities, thermal stabilities, storage stabilities, and processabilities. The ReA-NF-DAEs were able to be reused to catalyze the conversion from D-fructose to D-allulose, and kept more than 60% of their activities after eight cycles.

The tumor microenvironment (TME) is crucial in tumor development, metastasis, and response to immunotherapy. DNA methylation can regulate the TME without altering the DNA sequence. However, research on the methylation-driven TME in clear-cell renal cell carcinoma (ccRCC) is still lacking. In this study, integrated DNA methylation and RNA-seq data were used to explore methylation-driven genes (MDGs). Immune scores were calculated using the ESTIMATE, which was employed to identify TME-related genes. A new signature connected with methylation-regulated TME using univariate, multivariate Cox regression and LASSO regression analyses was developed. This signature consists of four TME-MDGs, including AJAP1, HOXB9, MYH14, and SLC6A19, which exhibit high methylation and low expression in tumors. Validation was performed using qRT-PCR which confirmed their downregulation in ccRCC clinical samples. Additionally, the signature demonstrated stable predictive performance in different subtypes of ccRCC. Risk scores are positively correlated with TMN stages, immune cell infiltration, tumor mutation burden, and adverse outcomes of immunotherapy. Interestingly, the expression of four TME-MDGs are highly correlated with the sensitivity of first-line drugs in ccRCC treatment, especially pazopanib. Molecular docking indicates a high affinity binding between the proteins and pazopanib. In summary, our study elucidates the comprehensive role of methylation-driven TME in ccRCC, aiding in identifying patients sensitive to immunotherapy and targeted therapy, and providing new therapeutic targets for ccRCC treatment.

Lithium metal batteries (LMBs) are anticipated to meet the demand for high energy density, but the growth of lithium dendrites seriously hinders its practical application. Herein, we constructed a kind of composite separator (ZIF-90@PP) consisting of zeolite imidazole framework-90 (ZIF-90) and polypropylene (PP) to promote the uniform deposition of Li+ and inhibit the growth of lithium dendrites. The aldehyde groups interacting with TFSI− and the nitrogen-containing negative groups attracting Li+ of ZIF-90 can facilitate the dissociation of LiTFSI to release more Li+, thus alleviating the influence of space charge near the electrode surface and accelerating the transfer of Li+. Not only does the excellent electrolyte wettability of ZIF-90 enhance the electrolyte retention capacity of the separator, but the orderly nano-channels in ZIF-90 also restrict the free migration of anions and homogenize the distribution of Li+. Consequently, the functional separator achieves a long-term stable Li plating/stripping cycling for over 780 h at 2 mA cm−2. Moreover, an impressive average coulombic efficiency of 98.67% at 0.5 C after 300 cycles is realized by Li || LFP full cells based on ZIF-90@PP with a capacity retention rate of 71.22%. The high-rate and long cycling performance of the modified Li || LFP cells further demonstrates the advantages of the ZIF-90@PP composite separator.

Abstract Molecular rotor‐based fluorophores (RBFs) activate fluorescence upon increase of micro‐viscosity, thus bearing a broad application promise in many fields. However, it remains a challenge to control how fluorescence of RBFs responds to viscosity changes. Herein, we demonstrate that the formation and regulation of intramolecular hydrogen bonds in the excited state of RBFs could modulate their rotational barrier, leading to a rational control of how their fluorescence can be activated by micro‐viscosity. Based on this strategy, a series of RBFs were developed based on 4‐hydroxybenzylidene‐imidazolinone (HBI) that span a wide range of viscosity sensitivity. Combined with the AggTag method that we previously reported, the varying viscosity sensitivity and emission spectra of these probes enabled a dual‐color imaging strategy that detects both protein oligomers and aggregates during the multistep aggregation process of proteins in live cells. In summary, our work indicates that installing intracellular excited state hydrogen bonds to RBFs allows for a rational control of rotational barrier, thus allow for a fine tune of their viscosity sensitivity. Beyond RBFs, we envision similar strategies can be applied to control the fluorogenic behavior of a large group of fluorophores whose emission is dependent on excited state rotational motion, including aggregation‐induced emission fluorophores.

Acoustic agglomeration is a technique that leverages on sound waves to promote the collision of aerosol particulate matter, thus leading to the formation of larger particle agglomerates. In this study, this acoustics-driven phenomenon is demonstrated for its usefulness as an aerosol pre-conditioning method to significantly enhance the efficiency of filtration systems in particle treatment processes. Specifically, favorable changes in pressure drop across the filters are observed as a result of receiving less particle mass, for which filters are shown to be able to have their operational life extended remarkably by more than 50%. The involved ultrasonic aerosol agglomeration mechanisms are unveiled through numerical simulations, and the effects of residence time, sound pressure level, and initial particle number concentration on agglomeration performances are experimentally investigated. In addition, validations and measurements of filter pressure drop are obtained through a series of experiments. This study provides a comprehensive overview to the design and performance characterization of acoustics-agglomeration-enhanced filtration systems, which could potentially derive energy savings for fan power in ventilation systems and be scaled up for applications in industrial plants for reducing carbon emissions.

Aconitine (AC), which is the primary bioactive diterpene alkaloid derived from Aconitum L plants, have attracted considerable interest due to its unique structural feature. Additionally, AC demonstrates a range of biological activities, such as its ability to enhance cardiac function, inhibit tumor growth, reduce inflammation, and provide analgesic effects. However, the structure-activity relationships of AC are remain unclear. A clear understanding of these relationships is indeed critical in developing effective biomedical applications with AC. In line with these challenges, this paper summarized the structural characteristics of AC and relevant functional and bioactive properties and the structure-activity relationships presented in biomedical applications. The primary temporal scope of this review was established as the period spanning from 2010 to 2023. Subsequently, the objective of this review was to provide a comprehensive understanding of the specific action mechanism of AC, while also exploring potential novel applications of AC derivatives in the biomedical field, drawing upon their structural characteristics. In conclusion, this review has provided a comprehensive analysis of the challenges and prospects associated with AC in the elucidation of structure-bioactivity relationships. Furthermore, the importance of exploring modern biotechnology approaches to enhance the potential biomedical applications of AC has been emphasized.

The capacity for nanopatterning and functionality is a promising facet of supramolecular self‐assembly. However, the formation of molecular frameworks entirely dependent on van der Waals (vdW) interactions is infrequently explored. Herein, 2D vdW supramolecular structures are synthesized through the self‐assembled cocrystallization of C60 and decanethiol (DT) molecules on Au(111) surface. Notably, the system eliminates the need of functional groups for specific bonding between adjacent units. The conformation C60/DT is delicately manipulated by adjusting molecular coverage and annealing temperature. The absence of directional bonding between C60 and DT molecules facilitates the formation of a variety of stable phases at room temperature (RT), such as 1) porous C60 networks with thiol‐filled pores and 2) self‐synthesized (C60)n nanochains with thiol spacers interspersed between the chains are achieved and visualized by scanning tunneling microscopic imaging under RT. This innovative integration of the vdW interaction unveils new avenues for developing supramolecular patterns characterized by their comparatively weak but exceptionally adaptable bonding.

Abstract Organic solar cells (OSCs) have attracted extensive attention from both academia and industry in recent years due to their remarkable improvement in power conversion efficiency (PCE). However, the Golden Triangle (the balance of efficiency‐stability‐cost) required for large‐scale industrialization of OSCs still remains a great challenge. Here, a new nonfused‐ring electron acceptor (NFREA) BF and its polymerized counterpart PBF were designed and synthesized, and their photovoltaic performance, storage stability and material cost were systematically investigated. When blended with a widely‐used polymer donor PBDB‐T, the PBF‐based all‐polymer solar cell (all‐PSC) displayed a record high PCE of 12.61% for polymerized NFREAs (PNFREAs) with an excellent stability (95.2% of initial PCE after 800 h storage), superior to the BF counterpart. Impressively, PBF‐based all‐PSC possesses the highest industrial figure‐of‐merit (i‐FOM) value of 0.309 based on an efficiency‐stability‐cost evaluation, in comparison to several representative OSC systems (such as PM6:Y6 and PBDB‐T:PZ1). This work provides an insight into the balance of efficiency, stability, and cost, and also indicates that the PNFREAs are promising materials toward the commercial application of OSCs.

Processing polyethylene terephthalate (PET) into functional materials has both sustainable and economic significance. Therefore, this study aims to prepare functional nanofibers using PET, combining electrospun nanofibers with metal–organic frameworks (MOFs), which is an effective solution to increase the added value of functional nanofiltration membranes (NFMs). The surface morphology of PET fibers is successfully controlled by electrospinning parameters and post-treatment. The formation of a uniform coating of CuBTC crystals on the PET surface is induced by a simple and low-cost in situ growth technique. CuBTC@PET was treated to prepare superhydrophobic CuBTC@PET (SCP), thus improving the stability of CuBTC in water and expanding its potential applications. Through a series of optical and thermal characterizations, the porous morphology formation mechanism and MOF in situ growth mechanism of SCP fibers were discussed. Then, the air filtration performance and bacteriostatic properties of SCP nanofiltration membranes were investigated. The as-prepared SCP showed a high water contact angle (146.4°), low-pressure drop (39.7 Pa), and high filtration efficiency (95.3%, 3 μm NaCl), as well as unique, broad-spectrum antibiosis potency against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). This study shows that SCP nanofiltration membranes can be practically applied in high-performance antibacterial filtration membranes.

Hybrid nanomaterials have attracted considerable interest in biomedicine because of their fascinating characteristics and wide range of applications in targeted drug delivery, antibacterial activity, and cancer treatment. This study developed a gelatin-coated Titanium oxide/palladium (TiO2/Pd) hybrid nanomaterial to enhance the antibacterial and anticancer capabilities. Morphological and structural analyses were conducted to characterize the synthesized hybrid nanomaterial. The surface texture of the hybrid nanomaterials was examined by high-resolution transmission electron microscopy (HR-TEM) and field-emission scanning electron microscopy (FE-SEM). The FE-SEM image revealed the bulk of the spherically shaped particles and the aggregated tiny granules. Energy dispersive X-ray spectroscopy (EDS) revealed Ti, Pd, C, and O. X-ray diffraction (XRD) revealed the gelatin-coated TiO2/Pd to be in the anatase form. Fourier transform infrared spectroscopy examined the interactions among the gelatin-coated TiO2/Pd nanoparticles. The gelatin-coated TiO2/Pd nanomaterials exhibited high antibacterial activity against Escherichia coli (22 mm) and Bacillus subtilis (17 mm) compared to individual nanoparticles, confirming the synergistic effect. More importantly, the gelatin-coated TiO2/Pd hybrid nanomaterial exhibited remarkable cytotoxic effects on A549 lung cancer cells which shows a linear increase with the concentration of the nanomaterial. The hybrid nanomaterials displayed higher toxicity to cancer cells than the nanoparticles alone. Furthermore, the cytotoxic activity against human cancer cells was verified by the generation of reactive oxygen species and nuclear damage. Therefore, gelatin-coated TiO2/Pd nanomaterials have potential uses in treating cancer and bacterial infections.

The immobilization of enzymes is an important strategy to improve their stability and reusability. Enzyme immobilization technology has broad application prospects in biotechnology, biochemistry, environmental remediation, and other fields. In this study, composites of chitosan (CS) and sodium alginate (SA) with Cu2+ forming a double-network crosslinked structure of hydrogels were prepared and used for the immobilization of laccase. Fourier infrared spectroscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy tests revealed that laccase molecules were immobilized on the composite hydrogel surface by a covalent bonding method. Compared to free laccase, the pH, temperature, and storage stability of the immobilized laccase were markedly improved. In addition, the immobilized laccase could be easily separated from the reaction system and reused, and it maintained 81.6% of its initial viability after six cycles of use. Bisphenol A (BPA) in polluted water was efficiently degraded using immobilized laccase, and the factors affecting the degradation efficiency were analyzed. Under the optimal conditions, the BPA removal was greater than 82%, and the addition of a small amount of ABTS had a significant effect on BPA degradation, with a removal rate of up to 99.1%. Experimental results indicated that immobilized laccases had enormous potential in actual industrial applications.

This study layed the groundwork for the creation of haploid and triploid celestial goldfish, presenting essential data derived from preliminary investigations. The research delved into three main areas: the short-term preservation of celestial goldfish gametes, the interaction between oocytes and foreign sperm, and the effects of temperature on fertilized eggs concerning hatching rates and late-stage ocular development. Initially, the study explored the optimal semen dilution ratio for celestial goldfish under microscopic examination. And the hybridization of the largemouth bass and celestial goldfish was investigated: largemouth bass sperm was crossbred with celestial goldfish eggs, and it was found that their sperm could not stimulate the development of celestial eye eggs. At last, celestial goldfish fertilized eggs were stimulated at 4 °C and −20 °C, respectively, to observe their impact on the hatching rate and later celestial eye rate. The results revealed no significant differences in hatching rate and celestial eye rate between the cold stimulus groups and the control group, but numerically, the 4 °C cold stimulation reduced the celestial eye rate of celestial goldfish fertilized eggs. The research provided fundamental data for artificial breeding and hybridization experiments in celestial goldfish.

Addressing the issues of weak echo signals and strong background interference in the laser detection of ships’ wakes, an analysis of the laser backscatter detection characteristics of ships’ wakes has been conducted. Based on the Monte Carlo method, a simulation model for the dual-mode fusion detection of ship wake bubbles using laser technology was constructed under different target characteristics. A dual-mode fusion detection system for ships’ wakes was designed, and an indoor experimental platform for the dual-mode fusion detection of ship wake bubbles using laser technology was established. To address problems such as a wide range of echo signal intensity changes, severe signal fluctuations, low resolution, poor image contrast, and blurred target edge information, an algorithm based on multi-timescale hierarchical fusion signal processing and temporal difference accumulation image processing was proposed. Verification experiments for ship wake detection were conducted, which revealed that the dual-mode fusion detection method for ship wake bubbles using laser technology can effectively enhance the detection signal-to-background ratio and counter the maneuvering evasion of underwater weapons by ships. It achieved high sensitivity, large dynamic range, high resolution, and a wide field of view detection and real-time signal processing of ship wake bubble targets of different magnitudes against a strong reverberation background. The effectiveness of the dual-mode fusion detection mode was validated, providing theoretical support for the overall system design and parameter settings.

As a crucial task for disease diagnosis, existing semi-supervised segmentation approaches process labeled and unlabeled data separately, ignoring the relationships between them, thereby limiting further performance improvements. In this work, we introduce a transformer-based multi-task framework that concurrently leverages both labeled and unlabeled volumes by encoding shared representation patterns. We first integrate transformers into YOLOv5 to enhance segmentation capabilities and adopt a multi-task approach spanning shadow region detection and boundary localization. Subsequently, we leverage the mean teacher model to simultaneously learn from labeled and unlabeled inputs alongside orthogonal view representations, enabling our approach to harness all available annotations. Our network can improve the learning ability and attain superior performance. Extensive experiments demonstrate that the transformer-powered architecture encodes robust inter-sample relationships, unlocking substantial performance gains by capturing shared information between labeled and unlabeled data. By treating both data types concurrently and encoding their shared patterns, our framework addresses the limitations of existing semi-supervised approaches, leading to improved segmentation accuracy and robustness.

Automatic image segmentation is vital for the computer-aided determination of treatment directions, particularly in terms of labelling lesions or infected areas. However, the manual labelling of disease regions is inconsistent and a time-consuming assignment. Meanwhile, radiologists’ comments are exceedingly subjective, regularly impacted by personal clinical encounters. To address these issues, we proposed a transformer learning strategy to automatically recognize infected areas in medical images. We firstly utilize a parallel partial decoder to aggregate high-level features and then generate a global feature map. Explicit edge attention and implicit reverse attention are applied to demonstrate boundaries and enhance their expression. Additionally, to alleviate the need for extensive labeled data, we propose a segmentation network combining propagation and transformer architectures that requires only a small amount of labeled data while leveraging fundamentally unlabeled images. The attention mechanisms are integrated within convolutional networks, keeping their global structures intact. Standalone transformers connected straightforwardly and receiving image patches can also achieve impressive segmentation performance. Our network enhanced the learning ability and attained a higher quality execution. We conducted a variety of ablation studies to demonstrate the adequacy of each modelling component. Experiments conducted across various medical imaging modalities illustrate that our model beats the most popular segmentation models. The comprehensive results also show that our transformer architecture surpasses established frameworks in accuracy while better preserving the natural variations in anatomy. Both quantitatively and qualitatively, our model achieves a higher overlap with ground truth segmentations and improved boundary adhesion.

Aiming at the problems of low power, low energy transmission efficiency, and high stress in the circuit of a single-phase wireless power transfer system, this paper proposes a wireless power transfer (WPT) system with a three-phase angle difference of 120 degrees and establishes a COMSOL multi-physics simulation model for analysis. In this simulation model, the topology of the three-phase resonant compensation network is studied in detail, and the structure of the coupling coil is designed and adjusted. Compared with the single-phase system with the same environmental conditions, air gap, and operating frequency, the simulation results show that the proposed three-phase system can effectively reduce the magnetic flux leakage, reduce the stress in the circuit, and significantly improve the energy transmission efficiency. In order to verify the reliability of the simulation results, an experimental platform was built. The experimental results show that the efficiency and coupling degree of the new system are significantly improved at the resonant frequency of 47.5 kHz, and the stress in the circuit is also significantly reduced.

This article aims to conduct an in-depth investigation into the environmental impact of Hall thruster plumes on spacecraft surface charging. The non-uniform plasma plume generated by Hall thrusters may trigger charging and discharging effects, making the assessment of surface charging risks crucial. Through numerical simulations using SPIS system, this study evaluates the surface charging characteristics of a complex spacecraft in orbit, simulating the effects of turning on and off the thrusters, as well as varying distances between the thrusters and the spacecraft. The simulation demonstrates that turning on the thrusters significantly affects spacecraft charging, reducing the potential difference between spacecraft surfaces from 3740 V to 19.2 V, effectively alleviating electrostatic discharge on the spacecraft surface. The closer the thruster is to the spacecraft, the more CEX ions are collected on the surface, influenced by the beam ions, resulting in a surface potential change of 1.3 V, with minor effects on surface potential but contributing to increased deposition contamination on the spacecraft surface.

Pepper anthracnose caused by Colletotrichum gloeosporioides infection is an important fungal disease and represents a serious threat to pepper yield and quality. At present, the pathogenic molecular mechanism of C. gloeosporioides is not very clear. In our study, we characterized the function of C. gloeosporioides CgNis1, a homolog of Magnaporthe oryzae MoNis1. We found that the ∆Cgnis1 mutant reduced the growth rate and was defective in conidiation. Although the rate of appressorium formation was unaffected, the germ tube was found to be abnormal. CgNis1 was shown to be involved in the H2O2 stress response and maintaining cell membrane permeability. The pathogenicity assays performed in this study indicated that the deletion of CgNIS1 is associated with virulence. Our results indicate that CgNis1 is necessary for the growth, development, and pathogenicity of the fungus. This work provides an in-depth analysis of the Nis1 protein, helps to enhance studies on pathogen-related molecular mechanisms, and provides a theoretical basis for the prevention and control of C. gloeosporioides in peppers.

A considerable amount of research on link prediction has recently been driven by missing relationships between knowledge graph entities and the problem of the incompleteness of knowledge graphs. Some recent studies have shown that convolutional neural networks based on knowledge embeddings are highly expressive and have good performance in link prediction. However, we found that the convolutional neural network (CNN)-based models do not handle the link between relations and entities well. For this reason, this paper proposes a link prediction model (LPM) based on feature mapping and bi-directional convolution. For the modeling of the task, an encoding layer–mapping layer–decoding layer structure is used. Among these layers, the encoding layer adopts a graph attention network to encode multi-hop triad information and obtains richer encoding of entities and relationships. The mapping layer can realize the mapping transformation between entities and relations and project the entity encoding in the space of relation encoding to capture the subtle connection between entities and relations. The decoding layer adopts bidirectional convolution to merge and decode the triples in a sequential inverse order, which makes the decoding layer model more advantageous in prediction. In addition, the decoding layer also adopts the r-drop training method to effectively reduce the distribution error generated by training between models and enhance the robustness of the model. Our experiments demonstrated the effectiveness of mapping relations, bidirectional convolution, and r-drop, and the accuracy of the proposed model showed significant improvements for each evaluation metric on two datasets, WN18RR and FB15k-237.

In a multi-document summarization task, if the user can decide on the summary topic, the generated summary can better align with the reader’s specific needs and preferences. This paper addresses the issue of overly general content generation by common multi-document summarization models and proposes a topic-oriented multi-document summarization (TOMDS) approach. The method is divided into two stages: extraction and abstraction. During the extractive stage, it primarily identifies and retrieves paragraphs relevant to the designated topic, subsequently sorting them based on their relevance to the topic and forming an initial subset of documents. In the abstractive stage, building upon the transformer architecture, the process includes two parts: encoding and decoding. In the encoding part, we integrated an external discourse parsing module that focuses on both micro-level within-paragraph semantic relationships and macro-level inter-paragraph connections, effectively combining these with the implicit relationships in the source document to produce more enriched semantic features. In the decoding part, we incorporated a topic-aware attention mechanism that dynamically zeroes in on information pertinent to the chosen topic, thus guiding the summary generation process more effectively. The proposed model was primarily evaluated using the standard text summary dataset WikiSum. The experimental results show that our model significantly enhanced the thematic relevance and flexibility of the summaries and improved the accuracy of grammatical and semantic comprehension in the generated summaries.

Atherosclerosis, a disease that mainly affects human blood vessels, can cause various cerebral ischaemic diseases such as coronary heart disease and peripheral arterial disease. However, conventional drugs for the treatment of atherosclerosis have the disadvantages of low bioavailability and high toxicity. Bowl-shaped particles not only have the excellent properties of traditional spherical particles, such as improved drug distribution, increased drug absorption, reduced drug toxicity and side effects, but also are easier to circulate in the blood for a long time, have reduced immune rejection and have a larger specific surface area. Chitosan/polycaprolactone bowl-shaped particles were prepared via electrostatic spraying, and the effects of precursor solution concentration and polymer ratio on particle morphology were investigated. Chitosan/polycaprolactone composite bowl-shaped particles containing hirudin were prepared under optimal parameters for sustained anticoagulation. The anticoagulant molecules of hirudin could be continuously released from the composite scaffold as the bowl particles degraded. The biocompatibility and haemocompatibility of the composite particles were assessed using mouse glial cells and rabbit blood, and the results showed that the cell viability of the drug-loaded particles was overall above 90% and the haemolysis rate was below 2%. By controlling the release rate of hirudin, bowl-shaped particles can achieve a long-term anticoagulant drug delivery system and have wider application potential as a novel blood contact material.

To analyze the rock-breaking characteristics of an arcing-blade cutter in cutting red sandstone, a two-cutter cutting model was established based on the finite element method. Then, the cutting processes of the arcing-blade cutter at penetrations of 2 mm, 4 mm, and 6 mm with different cutter spacings were investigated, and the changing rules of the rock-breaking load, rock crushing state, and rock-breaking efficiency were obtained. Subsequently, the obtained simulation results were validated through linear cutting experiments. The research results showed that, as the penetration of the arcing-blade cutter increased, the rock-breaking load also increased; specifically, under 2 mm penetration, the rock-breaking load remained stable, irrespective of the cutter spacing. However, under 4 mm and 6 mm penetration, the vertical and rolling force increased and then stabilized with an increase in the cutter spacing, while the lateral force decreased and then stabilized, attributed to the synergistic effect between the cutters. At 2 mm penetration, the absence of interaction between the cutting of two cutters in sequence resulted in two separate crushed areas on the rock surface. However, at 4 mm and 6 mm penetration, the rock ridge could be crushed under a smaller cutter spacing. Meanwhile, with an increase in the cutter spacing, the synergistic effect between the cutters diminished, causing the rock ridge between two cuttings to remain uncrushed. The specific energy at the 4 mm and 6 mm penetrations decreased initially with an increase in the cutter spacing, then increased, and eventually stabilized. The optimal cutter spacings at these penetrations were determined as 50 mm and 60 mm, respectively. Conversely, at 2 mm penetration, the specific energy remained almost unchanged with an increase in the cutter spacing, maintaining at a high level and resulting in a low efficiency in cutting rock.

Banana (Musa acuminate) has been popular among consumers worldwide due to its rich nutrients and minerals. However, bananas are highly susceptible to the physical and biological factors that lead to postharvest loss during transportation and storage. In this work, novel sodium alginate (SA) films incorporated with silver nitroprusside nanoparticles (AgNNPs) were prepared to extend the shelf life of bananas through antibacterial and antioxidant coating. The results exhibited that AgNNPs were cubical and that their size was L. monocytogenes, S. enterica, and E. coli at the concentration of 500 µg/mL. Moreover, during the storage of bananas, SA-AgNNPs nanocomposite coatings act as a barrier to microbial contamination and slow down the ripening of bananas. As a result, compared with SA-coated and uncoated bananas, SA-AgNNPs-coated bananas exhibited the lowest weight loss and lowest total bacterial colonies, thus greatly extending their shelf life. Particularly when coated with SA-AgNNPs films, total bacterial colonies (TBC) in the banana peel and pulp were as low as 1.13 × 103 and 51 CUF/g on the ninth day of storage, respectively. Our work offers an efficient strategy to improve the quality of bananas during the postharvest period, with extensive applications in fruit preservation and food packing.

The low-temperature-grown InGaAs (LT-InGaAs) photoconductive antenna has received great attention for the development of highly compact and integrated cheap THz sources. However, the performance of the LT-InGaAs photoconductive antenna is limited by its low resistivity and mobility. The generated radiated power is much weaker compared to the low-temperature-grown GaAs-based photoconductive antennas. This is mainly caused by the low abundance of excess As in LT-InGaAs with the conventional growth mode, which inevitably gives rise to the formation of As precipitate and alloy scattering after annealing. In this paper, the migration-enhanced molecular beam epitaxy technique is developed to grow high-quality (InAs)m/(GaAs)n short-period superlattices with a sharp interface instead of InGaAs on InP substrate. The improved electron mobility and resistivity at room temperature (RT) are found to be 843 cm2/(V·s) and 1648 ohm/sq, respectively, for the (InAs)m/(GaAs)n short-period superlattice. The band-edge photo-excited carrier lifetime is determined to be ~1.2 ps at RT. The calculated photocurrent intensity, obtained by solving the Maxwell wave equation and the coupled drift–diffusion/Poisson equation using the finite element method, is in good agreement with previously reported results. This work may provide a new approach for the material growth towards high-performance THz photoconductive antennas with high radiation power.

Tea plants have to adapt to frequently challenging environments due to their sessile lifestyle and perennial evergreen nature. Jasmonates regulate not only tea plants’ responses to biotic stresses, including herbivore attack and pathogen infection, but also tolerance to abiotic stresses, such as extreme weather conditions and osmotic stress. In this review, we summarize recent progress about jasmonaic acid (JA) biosynthesis and signaling pathways, as well as the underlying mechanisms mediated by jasmontes in tea plants in responses to biotic stresses and abiotic stresses. This review provides a reference for future research on the JA signaling pathway in terms of its regulation against various stresses of tea plants. Due to the lack of a genetic transformation system, the JA pathway of tea plants is still in the preliminary stages. It is necessary to perform further efforts to identify new components involved in the JA regulatory pathway through the combination of genetic and biochemical methods.

The pile-bucket composite foundation represents an innovative foundation form that surpasses the horizontal bearing performance of both single bucket-shaped foundations and pile foundations. The intricate interplay between piles and buckets introduces the complexity of the factors influencing the bearing performance of composite foundations under horizontal loads. In this paper, the indoor model tests were conducted to investigate the effects of relative density and pile-to-barrel diameter ratio on the horizontal bearing capacity and surrounding soil pressure of the pile-bucket composite foundation. A sensitivity analysis on the bearing characteristics of the pile-bucket foundation was performed using ABAQUS/CAE 2020 software. The results reveal a consistent variation in load–displacement curves across diverse diameter ratios of piles to buckets. The pile-bucket diameter ratio significantly impacts the horizontal bearing characteristics of the composite foundation. Reducing the pile-bucket diameter ratio improves the horizontal bearing capacity of the composite foundation. When the diameter ratio of piles to buckets diminishes to ≤0.317, the influence of this ratio on bearing performance becomes markedly pronounced. The displacement range of the surface soil decreases with an increase in relative density, while the influence depth of the surrounding soil of the composite foundation significantly decreases as the pile-to-barrel diameter ratio decreases.

Recently, object detection has become a research hotspot in computer vision, which often detects regular images with small viewing angles. In order to obtain a field of view without blind spots, fisheye cameras, which have distortions and discontinuities, have come into use. The fisheye camera, which has a wide viewing angle, and an unmanned aerial vehicle equipped with a fisheye camera are used to obtain a field of view without blind spots. However, distorted and discontinuous objects appear in the captured fisheye images due to the unique viewing angle of fisheye cameras. It poses a significant challenge to some existing object detectors. To solve this problem, this paper proposes a PGDS-YOLOv8s model to solve the issue of detecting distorted and discontinuous objects in fisheye images. First, two novel downsampling modules are proposed. Among them, the Max Pooling and Ghost’s Downsampling (MPGD) module effectively extracts the essential feature information of distorted and discontinuous objects. The Average Pooling and Ghost’s Downsampling (APGD) module acquires rich global features and reduces the feature loss of distorted and discontinuous objects. In addition, the proposed C2fs module uses Squeeze-and-Excitation (SE) blocks to model the interdependence of the channels to acquire richer gradient flow information about the features. The C2fs module provides a better understanding of the contextual information in fisheye images. Subsequently, an SE block is added after the Spatial Pyramid Pooling Fast (SPPF), thus improving the model’s ability to capture features of distorted, discontinuous objects. Moreover, the UAV-360 dataset is created for object detection in fisheye images. Finally, experiments show that the proposed PGDS-YOLOv8s model on the VOC-360 dataset improves mAP@0.5 by 19.8% and mAP@0.5:0.95 by 27.5% compared to the original YOLOv8s model. In addition, the improved model on the UAV-360 dataset achieves 89.0% for mAP@0.5 and 60.5% for mAP@0.5:0.95. Furthermore, on the MS-COCO 2017 dataset, the PGDS-YOLOv8s model improved AP by 1.4%, AP50 by 1.7%, and AP75 by 1.2% compared with the original YOLOv8s model.

Medical image registration is a fundamental and indispensable element in medical image analysis, which can establish spatial consistency among corresponding anatomical structures across various medical images. Since images with different modalities exhibit different features, it remains a challenge to find their exact correspondence. Most of the current methods based on image-to-image translation cannot fully leverage the available information, which will affect the subsequent registration performance. To solve the problem, we develop an unsupervised multimodal image registration method named DTR-GAN. Firstly, we design a multimodal registration framework via a bidirectional translation network to transform the multimodal image registration into a unimodal registration, which can effectively use the complementary information of different modalities. Then, to enhance the quality of the transformed images in the translation network, we design a multiscale encoder–decoder network that effectively captures both local and global features in images. Finally, we propose a mixed similarity loss to encourage the warped image to be closer to the target image in deep features. We extensively evaluate methods for MRI-CT image registration tasks of the abdominal cavity with advanced unsupervised multimodal image registration approaches. The results indicate that DTR-GAN obtains a competitive performance compared to other methods in MRI-CT registration. Compared with DFR, DTR-GAN has not only obtained performance improvements of 2.35% and 2.08% in the dice similarity coefficient (DSC) of MRI-CT registration and CT-MRI registration on the Learn2Reg dataset but has also decreased the average symmetric surface distance (ASD) by 0.33 mm and 0.12 mm on the Learn2Reg dataset.

Abstract Protein amyloid aggregation has been widely observed to occur and plays important roles in both physiological processes and pathological diseases. Remarkably, amyloid aggregates assembled by native proteins gain a variety of different biological activities, which cannot be adopted by the unassembled protein alone. Thus, it is important to investigate the molecular basis of self‐assembly of protein amyloid aggregates and how the aggregated protein structure determines its function. In the review, we firstly introduce our structural knowledge on how different amyloid proteins undergo conformational transition and assemble into amyloid aggregate, with the main focus on amyloid fibril, which is the major species of amyloid aggregate. Then, we elaborate how different structures of amyloid fibrils enable them to fulfill highly diverse functions in either physiological or pathological condition. Furthermore, we discuss the structural polymorph which is a very unique feature of amyloid fibril, and its implication in understanding the structure‐function relationship of amyloid fibrils. Finally, we point out the importance of applying and integrating new approaches for deepening the structure‐function study of amyloid fibrils and highlight the potential of designing amyloid fibril‐based functional bio‐nanomaterials for application.

In this study, the deep eutectic solvent based ultrasound-assisted extraction (DES-UAE) was investigated for the efficient and environmentally friendly extraction of Selaginella chaetoloma total biflavonoids (SCTB). As an extractant for optimization, tetrapropylaminium bromide-1,4-butanediol (Tpr-But) was employed for the first time. 36 DESs were created, with Tpr-But producing the most effective results. Based on response surface methodology (RSM), the greatest extraction rate of SCTB was determined to be 21.68 ± 0.78 mg/g, the molar ratio of HBD to HBA was 3.70:1, the extraction temperature was 57 °C, and the water content of DES was 22 %. In accordance with Fick's second rule, a kinetic model for the extraction of SCTB by DES-UAE has been derived. With correlation coefficients 0.91, the kinetic model of the extraction process was significantly correlated with the general and exponential equations of kinetics, and some important kinetic parameters such as rate constants, energy of activation and raffinate rate were determined. In addition, molecular dynamics simulations were used to study the extraction mechanisms generated by different solvents. Comparing the effect of several extraction methods on S.chaetoloma using ultrasound-assisted extraction and conventional methods, together with SEM examination, revealed that DES-UAE not only saved time but also enhanced SCTB extraction rate by 1.5–3 folds. SCTB demonstrated superior antioxidant activity in three studies in vitro. Furthermore, the extract could suppress the growth of A549, HCT-116, HepG2, and HT-29 cancer cells. Alpha-Glucosidase (AG) inhibition experiment and molecular docking studies suggested that SCTB exhibited strong inhibitory activity against AG and potential hypoglycemic effects. The results of this study indicated that a Tpr-But-based UAE method was suitable for the efficient and environmentally friendly extraction of SCTB, and also shed light on the mechanisms responsible for the increased extraction efficiency, which could aid in the application of S.chaetoloma and provide insight into the extraction mechanism of DES.

Abstract Aberrant protein aggregation leads to various human diseases, but little is known about the physical chemical properties of these aggregated proteins in cells. Herein, we developed a boron‐dipyrromethene (BODIPY)‐based HaloTag probe, whose conjugation to HaloTag‐fused proteins allows us to study protein aggregates using both fluorescence intensity and lifetime. Modulation of BODIPY fluorophore reveals key structural features to attain the dual function. The optimized probe exhibits increased fluorescence intensity and elongated fluorescence lifetime in protein aggregates. Fluorescence lifetime imaging using this probe indicates that protein aggregates afford different viscosity in the forms of soluble oligomers and insoluble aggregates in live cells. The strategy presented in this work can be extended to enable a wide class of HaloTag probes that can be used to study a variety of physical properties of protein aggregates, thus helping unravel the pathogenic mechanism and develop therapeutic strategy.

A novel series of thirty coumarin derivatives (4a ∼ r, 5a ∼ l) constituted by coumarin and cinnamic acid/benzoic acid through oxime linkage were synthesized and evaluated for their potential anti-tyrosinase activity. Among them, compound 5l exhibited outstanding anti-tyrosinase activity with IC50 of 3.04 ± 0.01 μM compared to 14.13 ± 0.80 μM of kojic acid. Kinetic study revealed compound 5l to be a reversible and uncompetitive tyrosinase inhibitor. 3D fluorescence and CD spectra results showed treatment of compound 5l lead to the conformational changes of tyrosinase. Molecular docking revealed the binding between compound 5l and tyrosinase. Furthermore, compound 5l inhibited melanin content and cellular tyrosinase activity both in B16F10 cells and zebrafish model with no toxicity effect. Taken together, our findings suggested that compound 5l could be used as potential candidate to relieve tyrosinase-related hyperpigmentation.