The core of eLoran ground-based timing navigation system is the accurate measurement of groundwave propagation delay. However, meteorological changes will disturb the conductive characteristic factors along the groundwave propagation path, especially for complex terrestrial propagation environment, and may even lead to microsecond-level propagation delay fluctuation, seriously affecting the timing accuracy of the system. Aiming at this problem, this paper proposes a propagation delay prediction model based on Back-Propagation neural network (BPNN) for complex meteorological environment, which realizes the function of directly mapping propaga-tion delay fluctuation through meteorological factors. Firstly, the theoretical influence of meteoro-logical factors on each component of propagation delay is analyzed based on calculation parame-ters. Then, through the correlation analysis of the measured data, the complex relationship be-tween the seven main meteorological factors and the propagation delay, as well as their regional differences are demonstrated. Finally, a BPNN prediction model considering regional changes of multiple meteorological factors is proposed, and the validity of the model is verified by long-term collected data. Experimental results show that the proposed model can effectively predict the propagation delay fluctuation in the next few days, and its overall performance is significantly improved compared with the existing linear model and simple neural network model. eLoran; meteorological factor; propagation delay prediction model; Back-Propagation neural network;

Vaccines trigger a complicated immunological response that includes B and T cells, with B cells producing antibodies. SARS-CoV-2 immunity weakens over time after vaccination. Discovering key changes in antigen-reactive antibodies over time after vaccination could help improve vaccine efficiency. In this study, we collected data on blood antibody levels in a cohort of healthcare workers vaccinated for COVID-19 and obtained 73 antigens in samples from four groups according to the duration after vaccination, including 104 unvaccinated healthcare workers, 534 healthcare workers within 60 days after vaccination, 594 healthcare workers between 60 and 180 days after vaccination, and 141 healthcare workers over 180 days after vaccination. An efficient machine learning based framework containing four feature selection methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, and maximum relevance minimum redundancy) and four classification algorithms (decision tree, k-nearest neighbor, random forest, and support vector machine) was designed to screen out essential antigens. Several efficient classifiers with weighted F1 value around 0.75 were constructed. This study revealed that S1+S2, S1.mFcTag, S1.HisTag, S1, S2, Spike.RBD.His.Bac, Spike.RBD.rFc, and S1.RBD.mFc were most highly ranked among all features, where S1 and S2 are the subunits of Spike, and the suffixes represent the tagging information of different recombinant proteins. Meanwhile, the classification rules were extracted from the optimal decision tree to explain quantitatively the roles of antigens in the classification. This study identified antibodies associated with decreased clinical immunity based on populations with different time spans after vaccination. These antibodies have important implications for maintaining long-term immunity to SARS-CoV-2.

Marine soft corals are prolific sources of various natural products that have served as a wealthy reservoir of diverse chemical scaffolds for new drug leads. The genus Litophyton contains almost 100 species but only a small part of them had been classified and chemically investigated, which calls for more attentions from the global researchers. In the current work, 109 secondary metabolites have been discussed based on published data from 1975 to July, 2023, covering a period of near five decades. The studied species of the genus Litophyton inhabited various tropical and temperate regions and afforded a variety of biologically active natural products such as terpenes, steroids, alkaloids, and lipids. A wide spectrum of pharmacological effects of these compounds had been evaluated, including cytotoxic, anti-HIV, antibacterial, antifungal, anti-malarial, antifeedant, molluscicidal, PTP1B inhibitory, and insect growth inhibitory activities. This review aims to provide an up-to-date literature survey and comprehensive insight into chemical structures, taxonomical distributions, and biological activities of the reported metabolites from the title genus whenever available.

Fifteen new diterpenoids, namely xishaklyanes A-O (1-15), along with three known related ones (16-18), were isolated from the soft coral Klyxum molle collected from Xisha Islands, South China Sea. The stereochemistry of the new compounds were elucidated by a combination of detailed spectroscopic analyses, chemical syntheses, quantum chemical calculations and comparison with the reported data. The absolute configuration of compound 18 was established by the modified Mosher's method for the first time. In bioassay, some of these compounds exhibited considerable antibacterial activities on fish pathogenic bacteria, and compound 4 showed the most effective activity with MIC of 0.225 g/mL against Lactococcus garvieae.

Based on the geologic conditions of natural gas hydrate (NGH) accumulations in the Shenhu area, northern slope of the South China Sea, this paper used a method of combining reservoir stimulation technique (RST) with depressurization to investigate the conversion efficiency of marine NGH reservoirs in different intrinsic permeability and initial NGH saturation conditions, and analyze the influence of variably-stimulation effect on marine NGH conversion efficiency in different accumulation conditions, provided a reference scheme for improving the NGH conversion efficiency in the Shenhu area. In this work, we performed calculations for the variations in CH4 production rate and cumulative volume of CH4 in different initial NGH saturation, intrinsic permeability and stimulation effect conditions, variance analysis and range analysis methods were used to analyze the significance of these key factors and their interaction, and investigated the sensitivity of stimulation effect on NGH conversion efficiency, respectively. The simulation results showed that stimulation effect have a significant influence on NGH conversion efficiency, and the influence of interaction between these three factors were not obvious. Possibly most important, we clarified an optimum stimulation effect for higher NGH conversion efficiency under different accumulation conditions, especially in low-permeability and high-saturation, which corresponding stimulation effect were different.

The achievement of reproductive competence in male mammals is dependent on the testis. Goat testis’ development and spermatogenesis involve physiological events with high complexity. In the current work, 6 testes were respectively collected from immature, sexually mature and physically mature Qianbei Ma goats (1, 6 and 12 months old, respectively). RNA-Seq was carried out to reveal changes in testis mRNA expression levels in Qianbei Ma goats at various developmental stages, and gene expression profiling at different ages was established. Totally 18 libraries were established for screening genes and pathways associated with testis development and spermatogenic processes. Totally 9,724 upregulated and 4,153 downregulated genes were identified between immature (I) and sexually mature (S) testes; 7 upregulated and 3 downregulated genes were detected between sexually mature (S) and physically mature (P) testes, and approximately 4% of genes were alternately spliced between the I and S groups. Selected genes were verified by qRT-PCR, in agreement with sequencing data indicating their reliability. Those genes have critical functions in various developmental stages of goat testicular development and spermatogenesis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were carried out to evaluate differentially expressed genes (DEGs). GO analysis suggested DEGs were involved in “reproduction process”, “channel activity” and “cell periphery part” between I and S, and in “ion transport process”, “channel activity” and “transporter complex part” between S and P. KEGG analysis indicated that pathways such as “glycerolipid metabolism”, “steroid hormone biosynthesis” and “MAPK signaling pathway” may be involved in testis development and spermatogenesis. Genes including IGF1, TGFB1, TGFBR1 and EGFR may regulate the development of the testis from immature to sexually mature, which may be key candidate genes for the development of goat testis. These findings provide novel insights into goat testicular development and spermatogenesis.

Nobel metal nanohole arrays have been used extensively in chemical and biological systems due to their fascinating optical properties. Gold nanohole arrays (Au NHAs) were prepared as surface plasmon polaritons (SPP) generators for the surface-enhanced sum-frequency generation (SFG) detection of 4-Mercaptobenzonitrile (4-MBN). The angle-resolved reflectance spectra revealed that the Au NHAs have three angle-dependent SPP modes and two non-dispersive localized surface plasmon resonance (LSPR) modes under different structural orientation angles (sample surface orientation). An enhancement factor of ~30 was achieved when the SPP and LSPR modes of the Au NHAs were tuned to match the incident visible (VIS) and output SFG, respectively. This multi-mode matching strategy provided flexible controls and selective spectral windows for surface-enhanced measurements, and was especially useful in nonlinear spectroscopy where more than one light beam involved. The structural orientation- and power-dependent performance demonstrated the potential of plasmonic NHAs in SFG and other nonlinear sensing applications, and provided a promising surface molecular analysis development platform.

Five new cembrane-type diterpenes, lobocalines A–E (1–5), and four new steroids, lobocalines F–I (9–12), along with six known related compounds (6–8 and 13–15) were isolated from the Yalong Bay soft coral Lobophytum catalai. The structures of the new compounds were elucidated by extensive spectroscopic analysis, NMR calculation with DP4+ analysis, time-dependent density functional theory-electronic circular dichroism (TDDFT-ECD) calculations, X-ray diffraction analyses, and the comparison with the reported spectroscopic data of known compounds. Further, with the aid of X-ray diffraction analysis, the structure of lobocrasol B (15) was firmly revised as 15a. In in vitro bioassays, compound 2 showed moderate antibacterial activities against fish pathogenic bacteria Streptococcus parauberis KSP28 and Phoyobacterium damselae FP2244 with minimum inhibitory concentration (MIC) values of 8.7 and 17.3 µg/mL, respectively. All the steroids exhibited antibacterial activities against the S. parauberis KSP28 with MIC values ranging from 12.3 to 53.6 µg/mL. Compounds 2, 7 and 14 have remarkable inhibitory effects on the hemolysin production of Staphylococcus aureus, while compounds 8–12 have medium inhibitory effects on the pyocyanin production in Pseudomonas aeruginosa.

Hemorrhagic shock is the primary cause of death in patients with severe trauma, and the development of rapid and efficient hemostatic methods is of great significance in promoting the life-saving of trauma patients. In this study, polycaprolactone (PCL) nanofiber membrane was prepared by electrospinning technology. The PCL-PDA loading system was developed by modifying the surface of polydopamine (PDA) inspired by mussel adhesion protein, and the efficient and stable loading of thrombin (TB) was realized on the premise of ensuring the bioactivity of TB. The new thrombin loading system overcomes the disadvantages of harsh storage conditions, poor strength, easy to fall off, and can use thrombin to start rapid coagulation cascade reaction, which has the characteristics of fast hemostasis, good biocompatibility, high safety and wide range of hemostasis. The physicochemical properties and biocompatibility of PCL-PDA-TB membrane were verified by scanning electron microscopy, cell proliferation test, cell adhesion test and extract cytotoxicity test. Red blood cell adhesion, platelet adhesion, dynamic coagulation time and animal models all verified the coagulation effect of PCL-PD-TB membrane. Therefore, PCL-PDA-TB membrane has great potential in wound hemostasis.

Three new cembranoids (1–3) and a new casbanoid (4), along with three known analogues (5–7), have been isolated from the soft coral Sinularia nanolobata collected off Ximao Island. The structures including the absolute configurations of new compounds were established by extensive spectro-scopic data analysis, time-dependent density functional theory/electronic circular dichroism (TDDFT-ECD) calculations and the comparison with spectroscopic data of known compounds. In in vitro bioassay, compounds 1 and 5 exhibited moderate cytotoxic activities against human erythroleukemia (HEL) cells line with IC50 values of 37.1 and 42.4 uM, respectively.

Chemical investigation of the Chinese soft coral Lobophytum sp. has resulted in the isolation of six new compounds, namely lobosteroids A–F (1–6), along with four known compounds. Their structures were determined by extensive spectroscopic analysis and comparison with the spectral data reported in the literature. Among them, the absolute configuration of 1 was determined by X-ray diffraction analysis. These steroids characterized by either the presence of an α,β-αꞌ,βꞌ-unsaturated carbonyl or an α,β-unsaturated carbonyl moiety in ring A, or the existence of a 5α,8α-epidioxy system in ring B, as well as diverse oxidation sites of side chains. The prelimi-nary antibacterial bioassay showed all compounds exhibited significant antibacterial activities against the fish pathogenic bacteria Streptococcus parauberis FP KSP28 and Phoyobacterium damselae FP2244 with all inhibition rates more than 90% at the concentration of 150 µM. And at the same concentration, compounds 2, 6–10 also displayed potent inhibitory effects against vancomy-cin-resistant Enterococcus faecium bacteria G7 with all inhibition rates more than 90%.

Novel coronavirus infection is a recent infective agent that causes severe potentially fatal pneumonia. The clinical presentation includes asymptomatic infection, severe pneumonia, and acute respiratory failure. Data pertaining to the clinical presentation of solid organ transplant recipients are scarce. Two cases of novel coronavirus infection in two recipients of renal transplant with variable clinical presentations and outcomes are reported. The first patient presented with progressive respiratory symptoms, acute renal failure, and passed away, whereas the second one, although presented with respiratory tract symptoms and hypoxemia remained stable and exhibited an excellent clinical recovery despite recent reception of thymoglobulin induction. This paper reports rare cases of novel coronavirus infection in renal transplant recipients. For an enhanced insight of the novel coronavirus infection and acute kidney injury on the clinical presentation, severity, and outcome in solid organ transplant recipients, further investigations are required.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley Value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley Value are impractical as they necessitate additional model training, leading to increased communication overhead. Moreover, participants’ data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data weakens the marginal effects of participants, which in turn affects model accuracy and leads to underestimated contribution measurements. Current works often overlook the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a noval aggregation weight, it enhances the accuracy of contribution measurement. Experiments on the MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.