Search Results (7,560)

The Landslide susceptibility assessment in complex mountainous terrain is frequently limited by static modelling frameworks that inadequately capture nonlinear deformation characteristics and temporally evolving hazard processes. To bridge this gap, a continuous-time dynamic assessment framework is proposed for Shazhou Town, Sichuan Province, integrating slowly moving scatterogram interferometric radar (S(BAS-InSAR))-derived deformation time series with Liquid Neural Networks (LNN). By incorporating a liquid time-constant architecture, the model accommodates irregular temporal sampling and captures non-stationary environmental responses through adaptive multimodal feature fusion. Analysis of long-term SBAS-InSAR observations (January 2021–May 2025) reveals distinctive deformation patterns, identifying eight active zones with maximum annual displacement rates of 107 mm yr⁻¹ and cumulative subsidence of 535.7 mm, which serve as critical dynamic inputs for the susceptibility model. Comparative experiments demonstrate that the LNN framework outperforms benchmark models (including LSTM, GRU, Random Forest, and SVM), achieving a coefficient of determination (R²) of 0.95 and an RMSE of 0.50. Furthermore, multi-temporal validation against 189 historical landslide records (2008–2025) confirms the model’s robustness, yielding a 91.5% capture rate within high-susceptibility zones. Interpretability analyses via SHAP and Layer-wise relevance propagation identify rainfall and vegetation cover as dominant dynamic controls, while characterising a distinct slope threshold effect at approximately 20°. These findings demonstrate that explicit continuous-time neural modelling enables physically consistent representation of irregular satellite acquisition intervals and delayed hydro-mechanical responses, thereby advancing landslide susceptibility assessment from static spatial classification toward dynamic state evolution inference under asynchronous Earth observation data streams. Full article

This study aimed to investigate the effects of different aerobic exposure durations on mycotoxin accumulation, nutritional quality changes, and microbial community dynamics of corncob silage. The experiment was divided into four groups: T0 (corncob silage fermented for 45 days without aerobic exposure), T4 (corncob silage exposed to air for 4 days), T8 (corncob silage exposed to air for 8 days), and T12 (corncob silage exposed to air for 12 days). The results showed that after aerobic exposure, the contents of dry matter (DM), crude protein (CP), water-soluble carbohydrates (WSC), Crude Ash, lactic acid (LA), and ammonia nitrogen (NH₃-N) in all exposed groups (T4, T8, T12) were significantly lower than those in the T0 group, whereas the contents of neutral detergent fiber (NDF), acid detergent fiber (ADF), propionic acid (PA), and butyric acid (BA) were significantly higher than those in the T0 group. Exposure to aerobic conditions for 12 days resulted in the four mycotoxins exhibiting levels significantly higher than those in the other groups, and notably, zearalenone (ZEN) and ochratoxin (OT) exhibited a continuous increase in concentration with the extension of aerobic exposure. Aerobic exposure increased bacterial diversity and fungal relative abundance, and significant separations were observed in both bacterial and fungal communities between the T0 group and the aerobic exposure groups. At the phylum level, Firmicutes was the dominant bacterial phylum in the T0 group, while Pseudomonadota became the dominant phylum after aerobic exposure. At the genus level, Lacticaseibacillus was the dominant bacterial genus in the T0 group, whereas Variovorax, Vibrionimonas, and Mycobacterium dominated the bacterial communities in the aerobic exposure groups. The relative abundance of the fungal phylum Ascomycota increased from 30% in the T0 group to 80~90% in the aerobic exposure groups; the dominant fungal genera shifted from Zygosaccharomyces to Albifimbria and Pichia. In conclusion, prolonged aerobic exposure elevates the concentrations of mycotoxins in corncob silage, reduces the nutritional quality, and induces significant shifts in both bacterial and fungal community compositions. Full article

The reconstruction of detrital flux, paleoclimate, paleosalinity, paleo-primary productivity, paleohydrodynamic conditions, and paleo-water depth enhances understanding of sedimentary processes and their drivers during deep-time greenhouse-icehouse transitions, such as the Eocene–Oligocene transition. This study uses detailed geochemical analyses of major oxides and trace elements in sediment samples collected from the Beni Suef Formation (Bartonian–Priabonian) and the Maadi Formation (Priabonian) in the southern Tethys shelf (Egypt, northeastern Desert). Detrital proxies, including Si/Al, Ti/Al, and Zr/Al, indicate an enhanced influx of terrigenous sediments in the middle portion of the Qurn Member of the Beni Suef Formation, as further supported by noticeable facies variations, particularly the transition from shale to coarser silt- and sand-sized fractions. Paleoclimate indicators (Sr/Ba, Rb/Sr, K₂O/Al₂O₃, and Sr/Cu) point to a climatic shift from humid to arid conditions, consistent with the regional Late Eocene aridification across the Tethyan realm. Paleosalinity proxies (Sr/Ba, Ca/Al, and Mg/Al×100) suggest episodic intensification of open-marine influence and a reduction in freshwater input, with an upsection increase in Sr/Ba ratios, reflecting phases of enhanced marine water settings or decreased terrestrial runoff. Primary productivity was evaluated using multiple geochemical proxies, including P, Ni/Al, Cu/Al, P/Al, P/Ti, and Babio ratios. These collectively indicate generally low primary productivity interrupted by intervals of enhanced paleoproductivity or increased organic matter export to the sediments. This interpretation is further supported by the low total organic carbon (TOC) values. These results highlight the sensitivity of the southern Tethys shelf to Middle–Late Eocene climatic variability and the key role of prevailing paleoenvironmental conditions in controlling sediment supply, water chemistry, and biological productivity. Full article

To address the range-angle coupling issue of frequency diverse array (FDA), a beamforming method based on subarray partitioning is proposed, with a focus on analyzing uniform continuous and nonuniform discontinuous subarray structures. Based on the transmit–receive signal model established to solve the time-varying issue of FDA, two subarray partitioning methods under the same array aperture are investigated. In the case of uniform continuous subarray structure, when different linear frequency offsets (FOs) are applied to each subarray, the mainlobe width in range dimension is 4.35 km, and the peak sidelobe level (PSLL) is −7.25 dB. When nonlinear FOs are applied, the mainlobe width is reduced to 2.76 km, and the PSLL is decreased to −9.64 dB. Furthermore, by adopting a nonuniform discontinuous subarray structure combined with nonlinear FOs, the mainlobe width is further narrowed to 1.29 km, and the PSLL is reduced to −11.75 dB. The simulation results demonstrate that under the same conditions, the nonuniform discontinuous subarray structure significantly improves range resolution and effectively suppresses sidelobe. Based on above results, a joint optimization combining the bat algorithm (BA) and K-means++ clustering algorithm is proposed to optimize the subarray structure and element amplitudes simultaneously. Finally, the mainlobe width of the optimized FDA is 1.18 km and the PSLL is −12.32 dB. Simulation results confirm the effectiveness and potential of the proposed method in enhancing range resolution and achieving a focused beampattern. Full article

Social media platforms contain rich but noisy narratives of psychological distress, creating opportunities for early mental health risk detection. However, existing datasets capture heterogeneous constructs such as suicide risk severity, depression diagnosis, and DSM-5 symptom presence, and most prior models are trained and evaluated on a single corpus, limiting their clinical alignment and cross-dataset generalizability. In this study, we fine-tune a domain-specific long-document transformer, AIMH/Mental-Longformer-base-4096, for binary mental health risk detection (risk vs. no risk) using two clinically aligned Reddit datasets: the C-SSRS Reddit corpus and the eRisk 2025 depression dataset. To handle long user histories, we introduce an LLM-based summarization pipeline that compresses posts exceeding 2000 tokens while preserving mental health-relevant information. We also conduct a seven-configuration ablation study across combinations of three corpora (C-SSRS, eRisk, and ReDSM5) to examine how dataset semantics influence model performance. On a held-out C-SSRS + eRisk test set (n = 279), the proposed model achieves a mean balanced accuracy of 0.89 ± 0.01 across five random seeds, with a best run of 0.90 and a 5.74 percentage point improvement over the strongest baseline (TF-IDF + Random Forest). The model also shows strong cross-platform generalization, achieving BA = 0.78 on the depression-reddit-cleaned dataset (n = 7731) and BA = 0.85 (ROC-AUC = 0.92) on a Twitter suicidal-intention dataset (n = 9119) without additional fine-tuning. The ablation analysis shows that although a three-dataset configuration (C-SSRS + eRisk + ReDSM5) maximizes aggregate performance, the ReDSM5 labels encode symptom presence rather than clinical risk, creating a semantic mismatch. This finding highlights the importance of label compatibility when combining heterogeneous mental health corpora. Explainability analysis using Integrated Gradients and attention visualization shows that the model focuses on clinically meaningful expressions such as therapy references, diagnosis, and hopelessness rather than isolated keywords. These results demonstrate that clinically aligned long-context transformers can provide accurate and interpretable mental health risk detection from social media while emphasizing the critical role of dataset semantics in multi-corpus training. Full article

Background and Objectives: Sclerostin or dickkopf-1 (DKK1) inhibits the canonical Wnt/β-catenin signaling pathway, which regulates vascular calcification and may contribute to the development of arterial stiffness. The brachial–ankle pulse wave velocity (baPWV) measures peripheral arterial stiffness (PAS). This study aimed to investigate the correlation between sclerostin and DKK1 levels and PAS in patients with type 2 diabetes mellitus (T2DM). Materials and Methods: Biochemical data and sclerostin and DKK1 levels were analyzed in the fasting blood samples of 125 patients with T2DM. baPWV measurements using the VaSera VS-1000 automatic pulse wave analyzer classified patients with values > 18.0 m/s on either side into the PAS group. Results: Among patients with T2DM, 47 (37.6%) were classified as having PAS. These patients exhibited higher hypertension prevalence (p = 0.002); greater age (p < 0.001); elevated systolic (p < 0.001) and diastolic blood (p = 0.012) pressures; and increased fasting glucose (p = 0.001), glycated hemoglobin (p = 0.008), triglyceride (p = 0.001), blood urea nitrogen (p < 0.001), and creatinine (p = 0.001) levels, urine albumin-to-creatinine ratio (p = 0.039), and C-reactive protein (p = 0.024) and serum sclerostin (p < 0.001) levels, but decreased estimated glomerular filtration rate (p < 0.001). Multivariate logistic regression analysis identified serum sclerostin level (odds ratio, 1.127; 95% confidence interval, 1.058–1.200; p < 0.001) as an independent PAS predictor in patients with T2DM. Serum log-transformed sclerostin levels were positively correlated with left (p = 0.005) and right (p = 0.001) baPWV via Spearman’s rank-order correlation coefficient analysis. Conclusions: Serum sclerostin levels, but not DKK1 levels, are positively correlated with PAS in patients with T2DM. Full article

This study explores the feasibility of using municipal solid waste incineration bottom ashes (MSWIBAs) as a partial replacement for cement in concrete with respect to the fresh and hardened properties of concrete. MSWIBA samples from five Swedish incineration plants (BA1–BA5) were collected and analyzed for their mineral composition and particle size distribution (PSD). The samples (BA3 and BA5), exhibiting better pozzolanic behavior and particle sizes closer to those of conventional cement, were selected for further detailed study. Mechanical activation was performed on the BA3 and BA5 samples. Concrete mixes were prepared with 10% and 20% (by mass) cement replacements utilizing raw and activated BA3 and BA5 samples. The resulting concrete specimens were evaluated through slump, density, and compressive strength tests at 7, 28, and 56 days. The results showed that activated MSWIBAs improved the workability of the concrete specimens compared with the control concrete mix, and the density of the concrete decreased with increasing the MSWIBA content. The compressive strength of the concrete mixes generally decreased as the replacement level of MSWIBAs increased. At 56 days, the concrete mix with 10% raw BA5 reached about 77% of the compressive strength of the control concrete mix, whereas mixes with 20% raw or activated MSWIBAs reached about 58%. The concrete mix with BA3 performed better than the mix with BA5 at 7 days, while the concrete mix with BA5 showed higher later-age compressive strength. In addition, mechanical activation of MSWIBAs did not significantly improve compressive strength of concrete mixes. Despite the reduction in compressive strength when using MSWIBAs, this sustainable concrete contributes to the development of climate-friendly concrete and offers potential environmental benefits. Full article

Bovine viral diarrhea virus (BVDV), a globally persistent pathogen, causes bovine viral diarrhea-mucosal disease (BVD-MD), a contagious bovine disease posing significant pressures on both public health and economic development. Baicalin (BA), a flavonoid derived from Scutellaria baicalensis, exhibits broad antiviral activities but suffers from poor aqueous solubility and low bioavailability, limiting its therapeutic potential against BVDV. To address this limitation, we developed BA-loaded poly (ethylene gly-col)-poly (lactic-co-glycolic acid) (PEG-PLGA) nanoparticles (BA-PEG-PLGA NPs). While autophagy and NLRP3 inflammasome activation have been individually implicated in viral pathogenesis, their functional crosstalk during BVDV infection remains uncharacterized. Herein, we evaluated the antiviral efficacy of BA-PEG-PLGA NPs through integrated in vitro and in vivo experiments. We employed quantitative polymerase chain reaction (qPCR), transcriptome sequencing, Western blot analysis, immunofluorescence microscopy, flow cytometry, and enzyme-linked immunosorbent assay (ELISA) to investigate the mechanisms by which BA and BA-PEG-PLGA NPs combat bovine viral diarrhea virus (BVDV) infection. We found that both free BA and BA-PEG-PLGA NPs effectively attenuated BVDV replication in vitro and in vivo; notably, the nano-formulation exhibited superior efficacy. Mechanistically, BA and its nano-formulation restored autophagy homeostasis, suppressed ROS overproduction, and blocked NLRP3 inflammasome activation and pyroptotic cell death effects comparable to the specific NLRP3 inhibitor MCC950. These findings establish the autophagy–NLRP3/pyroptosis axis as a critical pathogenic mechanism in BVDV infection and reveal that nano-formulated baicalin represents an antiviral strategy by coordinately targeting this axis. This work not only provides a translatable nanomedicine approach for BVDV control but also expands the mechanistic understanding of flavonoid-based interventions in viral inflammatory diseases. Full article

Rare earth elements (REEs) play a critical role in provenance tracing and the environmental reconstruction of the Earth. However, systematic investigations into the geochemical behavior and fractionation mechanisms of REEs during halite crystallization in brine–salt systems remain limited. This study reports new trace element and REE data for Late Cretaceous halites from the Thakhek Basin, Laos. Ratios of Sr/Ba, Sr/Cu, and V/Cr indicate a marine origin for the halites, which formed under hot climatic and oscillating oxidizing–anoxic redox conditions. Both primary and secondary halites display uniform Post-Archean Australian Shale (PAAS)-normalized REE distribution patterns, characterized by relative enrichment in medium rare earth elements (MREE) and depletion in light (LREE) and heavy rare earth elements (HREE). Similar REE patterns are also observed in halites from other modern and ancient, continental and marine salt basins worldwide. These observations suggest that the influences of parent brine composition and external provenance supplies on REE fractionation are negligible, given the consistent source, salinity, and redox conditions recorded in these halites. Accordingly, REE fractionation in halite was largely controlled by crystallographic effects, with aqueous MREE preferentially incorporated into halite crystals during deposition. In addition, the relatively lower Zr/Hf ratios in secondary halites compared to primary halites further validate the utility of the Zr/Hf ratio for distinguishing authigenic halite from salt modified by diagenesis, weathering, dissolution, or recrystallization. While our results establish a fundamental REE distribution pattern for halite, further research is needed to better constrain the underlying fractionation mechanisms of REEs in evaporite minerals within brine–salt systems. Full article

Tyrosine kinases (TKs) are drug targets in diffuse intrinsic pontine glioma (DIPG). Ion channels are emerging targets in cancer. TKIs targeting different kinases such as everolimus, crizotinib, dasatinib, erlotinib, lapatinib, perifosine and midostaurin (0.001–100 μM) were investigated on cell proliferation and ion channel currents. Methods: Cell viability assays in parallel with a patch-clamp study and Western blot of target proteins are performed in SU-DIPG-36 and SU-DIPG-50 cells. Results: Midostaurin is the most effective drug in different assays. Patch-clamp investigations show that the application of midostaurin reduced the inward and outward whole-cell cation channel currents vs. controls in the presence of low internal ATP. These currents were sensitive to the KATP channel inhibitors glibenclamide and repaglinide and were fully reduced by the unselective blocker TEA-BaCl₂. Midostaurin also reduced currents that are sensitive to TRPV1 channel blockers capsazepine and ruthenium-red. The IC₅₀ values of midostaurin as an antiproliferative drug and ion channel inhibitor in either cell line are in the sub-micromolar range. In SU-DIPG-36 cells midostaurin causes a concentration-dependent upregulation of autophagy markers. Conclusions: The inhibition of cation channel currents by midostaurin in SU-DIPG-36 and SU-DIPG-50 cells and the autophagy potentiation in SU-DIPG-36 cells can be novel mechanisms in DIPG. Full article

Background/Objectives: Emotions can be recognized through external behavioral cues and internal physiological signals. Owing to the inherently complex psychological and physiological nature of emotions, models relying on a single modality often suffer from limited robustness. This study aims to improve emotion recognition performance by effectively integrating electroencephalogram (EEG) signals and facial expressions through a multimodal framework. Methods: We propose a multimodal emotion recognition model that employs a Multi-Scale Dilated Attention Convolution (MSDAC) network tailored for facial expression recognition, integrates an EEG emotion recognition method based on three-dimensional features, and adopts a self-learning decision-level fusion strategy. MSDAC incorporates Multi-Scale Dilated Convolutions and a Dual-Branch Attention (D-BA) module to capture discontinuous facial action units. For EEG processing, raw signals are converted into a multidimensional time–frequency–spatial representation to preserve temporal, spectral, and spatial information. To overcome the limitations of traditional stitching or fixed-weight fusion approaches, a self-learning weight fusion mechanism is introduced at the decision level to adaptively adjust modality contributions. Results: The facial analysis branch achieved average accuracies of 74.1% on FER2013, 99.69% on CK+, and 98.05% (valence)/96.15% (arousal) on DEAP. On the DEAP dataset, the complete multimodal model reached 98.66% accuracy for valence and 97.49% for arousal classification. Conclusions: The proposed framework enhances emotion recognition by improving facial feature extraction and enabling adaptive multimodal fusion, demonstrating the effectiveness of combining EEG and facial information for robust emotion analysis. Full article

Introduction: Remote ischaemic conditioning (RIC) is a promising treatment for neurological disorders. It involves cycles of temporary ischaemic stimulus, usually applied to a limb, and has shown significant improvement in neurological function in many trials. This review focuses on identifying and summarising the biomarkers of RIC that can enhance clinical practice and understanding of its mechanisms. Methods: A search was conducted in MEDLINE and EMBASE up to August 2025 using terms related to ischaemic conditioning. Studies were included if they were RCTs involving cerebrovascular disease, used RIC as treatment, and measured mechanistic biomarkers. We extracted and summarised data on study design, participant characteristics, RIC intervention protocols (including timing, frequency, duration, and pressure), biomarker types and measurement methods, timing of biomarker assessment, and main findings relating biomarker changes to clinical outcomes. Results: The review identified twenty-one RCTs examining biomarkers, including serum biomarkers, imaging markers, and other physiological indicators. Key biomarkers identified include systemic inflammatory cytokines and various imaging markers such as cerebral blood flow (CBF), white matter hyperintensities (WMH), and brachial artery flow-mediated dilation (BA-FMD). Conclusions: The evidence suggests that RIC modulates various biomarkers linked to neuroprotection and recovery. Reliable biomarkers of RIC would enhance the understanding of its mechanisms and improve targeted therapies. The clinical utility of these biomarkers requires further validation through large-scale trials. Standardised protocols and longitudinal studies are essential for optimising RIC therapy and improving patient outcomes in stroke and cerebral small vessel disease. Future research should focus on expanding our understanding of these biomarkers and their interactions with RIC, leading to more personalised and effective treatments. Full article

The application of dual cytokinins can significantly enhance shoot multiplication rates in specific apple cultivars compared to standard protocols using a single cytokinin. This study presents a comprehensive analysis of shoot multiplication parameters and the underlying transcriptomic response of two distinct apple scion cultivars, cvs. Húsvéti rozmaring and McIntosh, to the simultaneous application of two cytokinins (BA and KIN). Morphological parameters were recorded, followed by comparative RNA-seq analysis and RT-qPCR validation. Our results demonstrate that the BA+KIN treatment induces a unique transcriptomic signature in both cultivars, which cannot be explained by a simple dose–response effect. In cv. McIntosh, 76% of the DEGs were uniquely regulated by the combination, while in cv. Húsvéti rozmaring, although the overlap with single treatments was higher, 17% of the DEGs (representing 1218 genes) were still exclusively activated by the BA+KIN treatment. The fact that the combined treatment recruits specific gene sets and metabolic pathways that remain silent under single BA or KIN applications—regardless of the cultivar—strongly supports a synergistic or non-additive hormonal interaction rather than a response to increased total cytokinin concentration. The dual treatment revealed 3209 DEGs in the inter-cultivar comparison, reflecting distinct strategies: cv. Húsvéti rozmaring achieved high efficiency growth by down-regulating internal hormones, whereas cv. McIntosh exploited intense auxin signaling and hormonal plasticity to maximize bud release. These results prove that distinct molecular pathways can lead to peak performance depending on the apple cultivar. Full article

Barbatic acid (BA), a phenolic compound isolated from Pyrrosia petiolosa (Christ) Ching, was investigated for its diuretic effects and underlying mechanisms following oral administration in rats using UPLC-MS/MS-based metabolomics and pharmacokinetics. In a water-loaded rat model, BA (28 and 56 mg/kg) significantly increased 6 h urine output (1.5-fold vs. model, p < 0.01) and promoted urinary excretion of Na⁺, K⁺, and Cl⁻ (1.1–1.4-fold, p < 0.05–0.01). Metabolomic analysis revealed that BA modulates amino acid metabolism pathways, including cysteine and methionine metabolism (impact score 0.16), tyrosine metabolism (impact score 0.10), histidine metabolism (impact score 0.12), taurine hypotaurine metabolismand (impact score 0.43), and phenylalanine metabolism (impact score 0.14). Pharmacokinetic evaluation showed dose-dependent half-lives of 5.88, 5.23, and 2.61 h at 28, 56, and 112 mg/kg, respectively, with Cmax and AUC increasing proportionally with dose (r² > 0.99). These findings provide the first integrated evidence supporting BA as a potential novel diuretic agent with a mechanism involving amino acid metabolism regulation. Full article

Background/Objectives: Influenza, RSV, and SARS-CoV-2 co-circulate and evolve under immune and therapeutic pressures, complicating decision-making for both vaccine formulation and antiviral use. Fragmented, pathogen-specific sequencing approaches limit cross-virus comparability. Methods: We applied a standardized, multiplexed, amplicon-based next-generation sequencing (NGS) workflow to 34 diagnostic specimens (Ct < 35) positive for influenza A/B, RSV-A/B, or SARS-CoV-2. Sequencing libraries were generated and run on an Illumina MiSeq platform (2 × 250 bp). Although the wet-lab workflow is standardized across pathogens, consensus generation and annotation utilized two different analysis environments: Geneious Prime for influenza and MicrobioChek for RSV and SARS-CoV-2. Quality metrics included genome breadth and depth of coverage. Results: Near-complete genomes (mean coverage ≥98%) were recovered for all samples. Influenza A(H1N1)pdm09 sequences clustered in clade 6B.1A; A(H3N2) clustered in subclade 3C.2a1b.2a.2; and influenza B belonged to the Victoria lineage V1A.3a.2. RSV sequences were assigned to Nextclade clades A.D.5.1, A.D.1.10, A.D.2.1, and A.D.3 (RSV-A) and to B.D.4.1.3 and B.D.E.1 (RSV-B), consistent with the ON1 (RSV-A) and BA (RSV-B) genotypes prevalent in recent seasons. Clinically relevant mutations included changes in the influenza HA site and neuraminidase substitutions, RSV F-protein polymorphisms, and spike protein substitutions associated with recent Omicron sublineages (L455F/S, F456L) in SARS-CoV-2. Conclusions: A unified amplicon–NGS approach yields harmonized genomic data across respiratory viruses, enabling timely detection of antigenic drift and resistance markers while supporting integrated, cross-pathogen surveillance. Full article