Search Results (690)

Since coming into full operation in 2020, the BeiDou-3 Navigation Satellite System (BDS-3) has provided global users with positioning, navigation and time-synchronization services. Satellite clock bias is a key factor that affects real-time precise point positioning (PPP), precise orbit determination and the optimization of navigation message parameters; high-precision prediction of clock bias is therefore critical for improving the accuracy and reliability of BDS-3. To further enhance the prediction accuracy and stability of satellite clock bias, we propose a hybrid model based on Mamba-LSTM. This combined model leverages the strengths of the Multimodal Adaptive Model Building Algorithm (Mamba) and the Long Short-Term Memory neural network (LSTM) to predict satellite clock bias. Using precise BDS-3 satellite clock bias data from the International GNSS Service (IGS), we carried out prediction experiments. First, we compared the proposed model’s predictive performance with that of the Mamba and LSTM models. In short-term (6 h) and long-term (24 h) prediction scenarios, the average prediction RMSE of Mamba-LSTM improved by approximately 41.7% and 48% relative to Mamba, and by approximately 50.4% and 54.7% relative to the LSTM results, respectively. Next, we ran comparison experiments against traditional neural networks—the BP model and the CNN model. In mid-term (12 h) and long-term (24 h) prediction scenarios, the average prediction RMSE of Mamba-LSTM improved by approximately 59.6% and 63.1% compared with BP, and by approximately 52.4% and 56.2% compared with CNN, respectively. The results indicate that the Mamba-LSTM hybrid model can significantly improve the accuracy and stability of satellite clock bias prediction. Full article

Molecular dynamics simulations were performed on 27 deep eutectic solvents (DESs) composed of various hydrogen bond acceptors (HBAs)—tetrabutylammonium bromide (TBAB), tetrabutylammonium chloride (TBAC), and tetraethylammonium chloride (TEAC)—combined with different hydrogen bond donors (HBDs)—3-aminopropan-1-ol (AP), 2-(methyl-amino)ethanol (MAE), and 2-(n-butylamino)ethanol (BAE). Radial distribution functions (RDFs) were computed from the simulation trajectories to probe the microscopic structure of these DESs. The effects of HBA/HBD molar ratio, alkyl chain length, anion type, and the amine group’s substitution on the structural organization of the DESs were systematically investigated. Moreover, the influence of water addition on the structural properties of selected DESs (TBAB with AP, MAE, or BAE at a 1:6 molar ratio) was explored. These structural features were then correlated with previously reported experimental data. To complement the classical simulations, ab initio molecular dynamics simulations were conducted on the same TBAB-based systems, enabling the analysis of electronic structure phenomena, including RDFs, dipole moment distributions, and charge transfer. Furthermore, experimental large-angle X-ray scattering (LAXS) data collection and analysis were performed in terms of the simulated structural data. This multi-scale approach provides a detailed understanding of the structural and electronic characteristics governing the behavior of alkanolamine-based DES. Full article

Candida albicans (C. albicans) is an opportunistic fungal pathogen capable of causing a wide range of infections, including mucosal and systemic candidiasis. In the oral cavity, fungi represent a minor component of the microbiome but can significantly contribute to morbidity, particularly under conditions of dysbiosis or immunosuppression. Treatment remains challenging due to increasing multidrug resistance. This study investigates the in vitro antifungal potential of Viroelixir, a standardized polyphenol blend derived from green tea and pomegranate and enriched in catechins (including epigallocatechin gallate, EGCG), ellagitannins (notably punicalagin), ellagic acid, and flavonoids, with particular focus on its potential anti-virulence mechanisms. Methods: The effect of Viroelixir on C. albicans growth was assessed using MTT assay, optical density measurements, colony formation, carbohydrate quantification, and pH variation analysis. Biofilm formation, morphological transition, ROS production, necrosis, virulence gene expression, adhesion, and host immune responses were also evaluated. Results: Viroelixir significantly inhibited C. albicans growth and reduced colony formation compared with untreated controls. The formulation also inhibited biofilm formation and markedly reduced pseudohyphal development, reaching up to 94% reduction under specific treatment conditions. Flow cytometry analysis showed an increase in dead fungal cells, reaching approximately 88% following exposure to Viroelixir at the highest tested concentration. In addition, Viroelixir reduced the transcript levels of several virulence-associated genes, including SAP1–SAP9 and EAP1. In epithelial cell co-culture models, pre-treatment of C. albicans with Viroelixir reduced fungal adhesion and attenuated epithelial inflammatory responses, including IL-6, IL-8, and hBD-2 production, and was associated with reduced activation of the TLR4-NF-κB signaling pathway. Conclusions: These findings suggest that the antifungal and anti-virulence effects observed may be associated with the polyphenolic compounds present in the Viroelixir formulation, highlighting its potential as a promising in vitro antifungal candidate against C. albicans. Full article

The efficacy of postbiotics varies significantly between different strains and preparation processes. We aimed at evaluating the effect of an innovative postbiotic product (iPB) generated through the sequential fermentation of Lacticaseibacillus rhamnosus GG and Lacticaseibacillus paracasei NPB-01, compared to single-strain postbiotics, on epithelial barrier integrity and innate immunity in human enterocytes using a Caco-2-cell-based experimental model by measuring human enterocyte proliferation and differentiation (lactase expression), tight junction proteins (occludin and zonula occludens 1, ZO-1), and mucus protein Mucin-2 (Muc-2) expression. The modulatory action on the major innate immunity peptide, Human Beta-Defensin 2 (HBD-2), production was also assessed. The iPB exposure resulted in a higher up-regulation of human enterocyte proliferation and differentiation, as suggested by higher lactase expression, and of occludin, ZO-1, and MUC2 expression compared with the single-strain postbiotics, suggesting a beneficial synergistic action in modulating the epithelial gut barrier. Furthermore, iPB induced a higher production of HBD-2, suggesting a synergistic enhancement of innate immune response. Our findings suggested that the sequential fermentation process could act as a biotechnological catalyst, optimizing the gut-barrier-protective properties and the immunomodulatory action of Lacticaseibacillus strains. This study introduces iPB as a high-performance postbiotic candidate for the prevention and management of conditions characterized by alterations in epithelial gut barrier and innate immunity. Full article

The latest H266/VVC standard has received numerous praises for its excellent compression efficiency. However, its extremely high computational complexity has become a hindrance to the VVC adaptation industry ecosystem, while also increasing the difficulty of hardware design and application costs. To address this issue, we designed an efficient intra-coding scheme based on neural networks, which consists of three parts: Firstly, we designed a neural network-based reverse prediction algorithm that uniquely utilizes the CNN’s prediction results for lower-level blocks to determine the QTMT partitioning of upper-level blocks, cleverly solving the adaptation problem of existing models to complex VVC partitioning patterns—a decision-making logic that has not been fully explored. Secondly, we designed a pruning algorithm, which is the first to dynamically couple the real-time RDO cost of BT segmentation with the TT segmentation direction, achieving adaptive decision-making. Finally, we designed a complexity pre-screening module. On the basis of analyzing whether the CU texture is smooth, this module designs four sets of adaptive thresholds for non-square CUs introduced in VVC. These thresholds can dynamically adjust local and global thresholds based on CU size, enabling size sensitive texture evaluation to determine whether the current block needs further partitioning. The experimental results show that, compared with traditional VTM4.0, our method reduces the average encoding time by 49.21%, while the BD-BR increase is 1.61%, and the BD-PSNR decreases by 0.06 dB, fully demonstrating its superiority and performance balance. Full article

Soil erosion assessment in Southeast Europe’s mountainous regions often lacks systematic field validation, limiting confidence in model-based predictions. This study integrates the Erosion Potential Model (EPM) with remote sensing and field verification across 26,570 km² in the Federation of Bosnia and Herzegovina (FBiH) and Brčko District (BD). We developed a two-stage framework: initial GIS-based assessment using digital elevation models, soil maps, climate data, CORINE Land Cover, and Landsat imagery, followed by field calibration at 190 representative sites. Spectral indices (NDVI, BSI) provided dynamic corrections for vegetation cover and visible erosion features. Field validation significantly improved model performance; the erosion coefficient increased from Z = 0.21 to Z = 0.24, while discriminatory power improved AUC from 0.82 to 0.85, with corresponding gains in overall accuracy from 0.78 to 0.84 and F1-score from 0.78 to 0.85. The field-validated model estimated mean annual sediment production of 546.60 m³·km⁻²·year⁻¹, with total erosion material production of 14,074,940.2 m³·year⁻¹. Field calibration revealed substantial spatial redistribution, with medium-to-excessive erosion categories expanding by 30.37%, affecting 1319.12 km² requiring priority intervention. The Kappa coefficient (0.81) confirms high classification reliability. This field-validated framework enables evidence-based identification of degradation hotspots and provides actionable guidance for soil conservation planning in geomorphologically heterogeneous, data-limited regions. Full article

Timely and accurate monitoring of surface water dynamics via remote sensing is critical, given water resources’ importance. However, accurate water body delineation based on high-resolution remotely sensed imagery is still challenging due to the complexity of water bodies’ boundaries and the diversity of their shapes and sizes, which can lead to boundary ambiguity and varying degrees of confusion with near-water vegetation in water body maps. To address this challenge, we introduce an uncertainty-aware hybrid CNN–Transformer model for delineating water bodies using remotely sensed imagery. In our designed network, a multi-scale transformer (MST) module is first designed to effectively model and refine the multi-scale global semantic dependencies of water bodies. Subsequently, an uncertainty-guided multi-scale information fusion (MSIF) module is constructed to extract water body mapping information from these multi-scale features output from the MST module and fuse them adaptively. Across different scales, the extracted features differ in their ability to distinguish water bodies from non-water bodies and in their levels of uncertainty. Consequently, during the adaptive fusion of multi-scale water body information in the MSIF module, the mapping uncertainty is quantified and suppressed to minimize its impact, thus yielding enhanced precision in water body delineation. Ultimately, a comprehensive loss function is designed for model optimization to generate the final water body map. Furthermore, to promote water body segmentation models’ development, this study also presents the HBD_Water water body sample dataset, which contains 44 multispectral, 5000 × 5000-pixel images at 2 m spatial resolution, and will be released on the LuojiaSET platform soon. Finally, to verify the proposed model and its constituent MST and MSIF modules, extensive water mapping experiments were performed on three datasets. The experimental results substantiate their effectiveness. Furthermore, comparative experiment results demonstrate that the proposed model performs better at water body extraction than advanced networks including TransUNet, DeeplabV3+, and ADCNN. Full article

Video coding plays a critical role for efficient transmission in surveillance camera sensors. Although long-term reference (LTR) has been fully studied in traditional hand-designed video coding approaches, its potential in learned video coding is still unexplored due to the highly unequal importance between long and short motion and the excessive motion overhead, especially for dense motion representation, e.g., optical flow. In this paper, we build an LTR baseline for learned surveillance video coding and propose an adaptive long–short modeling approach to address the above problem. Specifically, we first introduce LTR and propose a long–short context mining module to the authorized end-to-end video coding exploration model (EEM) from China’s AVS as a baseline. Since the quality of LTR significantly impacts its performance and importance, it is subsequently enhanced. Then, we propose a long–short motion adapter to address the unequal importance. Finally a historical motion guidance module is introduced to aid the motion decoding. Experimental results demonstrate that the proposed approach improves from a 1.86% BD-rate loss on EEM-4.1 to 13.89% BD-rate savings in YUV-PSNR compared with the anchor H.266/VVC under a low-delay P configuration. Although the current results are not comparable to the 44.01% gains of DCVC-FM, the proposed approach consumes less computational resources and we believe that integrating the proposed LTR method with stronger baselines will further boost the performance. Full article

Natural products from plants have played an important role in cancer and neurodegenerative diseases. In this context, the root bark of Maytenus chiapensis (Celastraceae) was investigated to examine its chemical constituents and potential biological activities. Chromatographic separation of the root bark extract yielded a new Diels–Alder adduct (morenine) formed by a triterpenophenolic moiety derived from tingenone and a bicyclic guaiane-type sesquiterpene linked through a 1,4-dioxane bridge. In addition, eight previously reported Diels–Alder adducts—retusonine and cheiloclines A–D and F–H—were isolated, together with their biosynthetic precursors, the quinone-methide triterpenoids (QMTs) pristimerin and tingenone. Structural elucidation was achieved through detailed 1D and 2D NMR spectroscopic analyses. The adducts were tested for cytotoxicity against six cancer cell lines (A549, SW1573, MIA PaCa-2, T-47D, HeLa, and WiDr cell lines), showing moderate-to-low activity compared with their precursors. Continuous live cell imaging identified apoptosis and vacuole formation as the main modes of action of pristimerin in SW1573 cells. Moreover, acetylcholinesterase inhibition assays revealed that cheiloclines B–D, F, and H exhibited up to 50% inhibition. These findings reinforce the potential of Celastraceae species as a source of unique and complex compounds and enhance our understanding of their therapeutic potential. Full article

The efficiency of six deep eutectic solvents (DESs) based on choline chloride (ChCl) and various hydrogen bond donors (HBDs) was evaluated against a traditional organic solvent for extracting polyphenolic bioactive compounds from three different white mulberry samples (Morus alba), including branches, leaves, and fruits. Ultrasound-assisted extraction was performed under selected conditions identified for ChCl/glycerol DES: a 1:2 molar ratio of hydrogen bond acceptor to HBD, 20% water added to the DES, a temperature of 80 °C, and an extraction time of 30 min, providing a set of standard parameters for comparing the efficiency of different DESs. Extraction efficiencies were assessed using a developed and validated HPLC method, as well as total phenolic content and total flavonoid content assays. Among the tested DESs, those composed of ChCl and polyalcohols as HBDs showed the best performance. For branch and leaf samples, the ChCl/glycerol DES was the most effective, while for fruit samples, the ChCl/ethylene glycol DES showed the highest efficiency. In most polyphenol extractions tested, at least one DES achieved extraction efficiencies comparable to or higher than those obtained with methanol, except for flavonoids, for which DES yields were often lower. Overall, the results indicate that using DESs represents a greener and more sustainable approach to extracting bioactive compounds from white mulberry. Full article

Vegetation restoration can regulate soil microbial habitat and carbon supply by altering soil physicochemical properties. However, it remains unclear how different vegetation restoration patterns influence soil microbial carbon cycling functions through these changes. This study investigated four vegetation restoration models including two coniferous forests —Platycladus orientalis (L.) Franco. (Cupressaceae, PO) and Pinus densiflora Siebold and Zucc. (Pinaceae, PS); one broadleaf forest—Quercus acutissima Carruth. (Fagaceae, QA); and a shrub (SH), using wasteland (WL) as a control. This study employed metagenomic sequencing technology in conjunction with analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The research examined alterations in soil physicochemical characteristics, microbial community structure, and functional pathway associated with carbohydrate metabolism, carbon fixation, and methane metabolism. Vegetation restoration patterns had a strong impact on soil characteristics and microbial composition. Compared to WL, the PO treatment exhibited significant increases in soil organic carbon (SOC, 110.71%), phosphorus (TP, 400%), and bulk density (BD, 22.4%). Significant differences were observed in soil carbon cycle functional pathways, with overall abundance following the trend PO > WL > SH > PS > QA. The relative abundance of carbon fixation, methane metabolism, and carbohydrate metabolism pathways was highest in PO, significantly higher than in QA. Mantel test showed soil phosphorus, pH, and C; N strongly linked to microbial carbon cycling pathways, marking them as key regulators. We found that PO showed the highest abundance of carbon-cycling-related functional pathways, whereas PS showed a comparatively weaker response, suggesting species-specific variation rather than a uniform coniferous–broadleaf pattern. Vegetation restoration controls microbial carbon cycling through soil properties, especially phosphorus, pH, and nutrient balances. This knowledge supports better restoration planning for ecosystem carbon management. Full article

This study used Global Navigation Satellite System (GNSS) observations from the China Crustal Movement Observation Network (CMONOC) and the Kunming Continuously Operating Reference Station (KMCORS) network to investigate ionospheric response characteristics over China during the geomagnetic storm of 4–6 November 2023, and to assess their impacts on CORS-based real-time kinematic (RTK) positioning performance in the low-latitude Kunming region. A quantitative assessment was conducted by integrating regional two-dimensional dTEC (%) maps over China, BeiDou Navigation Satellite System (BDS) Geostationary Earth Orbit (GEO) total electron content (TEC), the rate of TEC index (ROTI), and RTK positioning solutions to evaluate ionospheric disturbances, irregularity activity, and associated degradation in positioning performance. Results indicate that, during geomagnetic storms, ionospheric responses over China exhibit pronounced phase-dependent and latitudinal variations. During the second geomagnetic storm on 5–6 November, positive responses were dominant at mid-to-high latitudes, whereas alternating positive and negative responses were observed at low latitudes. During the recovery phase, the Kunming region successively experienced a positive ionospheric storm lasting approximately 10 h, followed by a negative ionospheric storm lasting about 7 h, with relative TEC variations reaching a maximum of approximately 90%. The GEO TEC time series was consistent with the temporal evolution of the two-dimensional dTEC (%), while ROTI increased markedly during the disturbance enhancement period (21:00 UT on 5 November to 07:00 UT on 6 November 2023). During periods of enhanced ionospheric response and irregularities, RTK positioning performance was observed to deteriorate markedly. The fixed-solution rate at medium-to-long baseline stations decreased from nearly 100% to close to 0%, accompanied by an increase in vertical positioning errors to approximately 20 cm, whereas short-baseline stations were only minimally affected. These results indicate that ionospheric disturbances during geomagnetic storms exert a pronounced impact on CORS-based RTK positioning services in the Kunming region, with the magnitude of this impact being closely related to baseline length. Full article

Background: Crimean-Congo hemorrhagic fever (CCHF) is a severe tick-borne viral disease with a high fatality rate, and no licensed vaccines are currently available. The nucleoprotein (NP) of the Crimean-Congo hemorrhagic fever virus (CCHFV) plays a critical role in viral replication and immune recognition, making it a promising target for vaccine development. This study aimed to design and evaluate a multiepitope recombinant DNA vaccine targeting the NP of CCHFV. Methods: Cytotoxic T lymphocyte (CTL) epitopes from the NP were predicted via immunoinformatics approaches and systematically assessed for antigenicity, allergenicity, toxicity, hydrophobicity, and global population coverage. The selected epitopes were incorporated into four DNA vaccine constructs driven by a cytomegalovirus promoter, adjuvanted with human β-defensin 3 (hBD3), and fused to the reporter protein mRuby3. The constructs were evaluated in vitro using a fluorescent reporter system designed to provide a readout of TCR signaling upon the co-culture of T lymphocytes with differentiated monocytic cells expressing antigens. In vivo immunogenicity and protective efficacy were assessed in BALB/c (exploratory pilot) and IFNAR^−/− mice, a highly susceptible model for viral infection. Cytokine responses were measured to assess immunogenicity. Results: In vitro assays showed predominantly antigen-independent T-cell activation, suggesting that nonspecific stimulation inherent to the reporter co-culture system likely obscured the detection of antigen-specific TCR signaling. In vivo analyses in BALB/c mice revealed that the constructs elicited only modest systemic cytokine profiles while CCHFV-specific IgG and IFN-γ secretion remained undetectable, indicating that antigen-specific T-cell and antibody responses were limited. In the IFNAR^−/− challenge model, several peptide groups achieved significant 2–3 log reductions in tissue viral RNA and infectious titers (p < 0.05 vs. sham). However, the observed viral modulations were insufficient to reach the protective threshold and did not translate to a survival benefit (0%). Conclusion: Despite a rational in silico foundation, the multiepitope DNA vaccine constructs demonstrated limitations in inducing potent, antigen-specific immunity across both mouse models. The lack of antigen-specific responses indicates limitations in epitope selection, construct design, and delivery strategies, requiring optimization of next-generation epitope-based vaccines. These findings highlight the complexity of translating computational epitope predictions into functional vaccines, and provide benchmark data as a framework to guide future optimizations. Full article

Pseudomonas aeruginosa causes severe healthcare-associated infections, yet no vaccine has been licenced. To circumvent the antigenic variability of classical surface antigens, we evaluated LolB—an essential outer-membrane lipoprotein whose periplasmic orientation favours T-cell-dominant mechanisms with potential antibody access via outer-membrane vesicles (OMVs) or bacteriolysis. An integrative in silico pipeline combined multi-strain conservation (20 isolates), epitope discovery (B- and T-cell), safety filters, physicochemical profiling, de novo/refined 3D modelling, molecular dynamics (MD), and docking to TLR4/MD-2. LolB was highly conserved (95–100% identity) under strong purifying selection (dN/dS = 0.15). A conformational B-cell hotspot centred on Q72 mapped to a solvent-accessible flexible loop. Two class II epitopes—LAAQNSPLT and FLGSAAAVS—showed predicted high affinity (IC₅₀ < 10 nM), non-toxicity, and broad coverage, with the pooled set achieving 98.6% global HLA coverage in silico. The final 119-aa construct (N-terminal hBD-3 adjuvant; GPGPG linkers) was compact and tractable (MW = 12.7 kDa; instability index < 40; near-neutral GRAVY) and scored higher for antigenicity than native LolB (VaxiJen 0.82 vs. 0.41). MD supported thermal stability up to 350 K, linker RMSF < 1.5 Å, and a stable 18.2 ± 2.8 Å interdomain spacing. Docking predicted a 1420 Ų interface and ΔG = −10.2 kcal·mol⁻¹ (Kd = 28 nM) with reproducible polar contacts, suggesting productive TLR4/MD-2 engagement. A conservative R42A/K variant is proposed to temper IFN-γ bias. This work therefore suggests an essentiality-anchored LolB-derived multi-epitope construct as a computational vaccine candidate against multidrug-resistant P. aaeruginosa and defines specific experimentally testable hypotheses for future in vitro/in vivo assessment. Essentiality-anchored epitope selection plus adjuvant-surface engineering yielded a structurally coherent, immunologically rational LolB-derived multi-epitope vaccine warranting experimental validation. Full article

Inbreeding is a quantitative measure of autozygosity that underlies the assessment of genetic risks and the management of genetic progress in livestock populations. The development of methods for its estimation reflects a transition from probabilistic pedigree-based models to the direct analysis of genome structure. This review systematizes the evolution of approaches to inbreeding assessment—from the classical inbreeding coefficient F based on identity by descent (IBD) to marker-based, segment-based runs of homozygosity (ROH) and probabilistic homozygous-by-descent (HBD) models. It is shown that the coefficients F_ped, F_GRM, F_ROH, and F_HBD capture related but distinct aspects of autozygosity and are therefore not fully interchangeable. Particular attention is paid to the transition from integral indicators to spatially and temporally stratified analyses of autozygosity, enabling the differentiation between ancient and recent inbreeding. Methodological assumptions, limitations, and the sensitivity of various approaches to marker density, detection parameters, and population demographic structure are discussed. A comparative analysis of methods for calculating F_ROH and segment-based autozygosity is presented. The necessity of a comprehensive assessment of inbreeding and the standardization of analytical protocols for its application in modern breeding programs is substantiated. Full article