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Deep learning-based landslide detection in optical remote sensing images has been extensively studied. However, several challenges remain. Over time, factors such as vegetation cover and surface weathering can weaken the distinct characteristics of landslides, leading to blurred boundaries and diminished texture features. Furthermore, obtaining landslide samples is challenging in regions with low landslide frequency. Expanding the acquisition range introduces greater variability in the optical characteristics of the samples. As a result, deep learning models often struggle to achieve accurate landslide identification in these regions. To address these challenges, we propose a multi-scale target attention YOLO model (MSTA-YOLO). First, we introduced a receptive field attention (RFA) module, which initially applies channel attention to emphasize the primary features and then simulates the human visual receptive field using convolutions of varying sizes. This design enhances the model’s feature extraction capability, particularly for complex and multi-scale features. Next, we incorporated the normalized Wasserstein distance (NWD) to refine the loss function, thereby enhancing the model’s learning capacity for detecting small-scale landslides. Finally, we streamlined the model by removing redundant structures, achieving a more efficient architecture compared to state-of-the-art YOLO models. Experimental results demonstrated that our proposed MSTA-YOLO outperformed other compared methods in landslide detection and is particularly suitable for wide-area landslide monitoring. Full article

Multivariate time series forecasting requires modeling complex and evolving spatio-temporal dependencies as well as frequency-domain patterns; however, the existing Transformer-based approaches often struggle to effectively capture dynamic inter-series correlations and disentangle relevant spectral components, leading to limited forecasting accuracy and robustness under non-stationary conditions. To address these challenges, we propose TSGformer, a Transformer-based architecture that integrates multi-scale adaptive graph learning, adaptive spectral decomposition, and cross-scale interactive fusion modules to jointly model temporal, spatial, and spectral dynamics in multivariate time series data. Specifically, TSGformer constructs dynamic graphs at multiple temporal scales to adaptively learn evolving inter-variable relationships, applies an adaptive spectral enhancement module to emphasize critical frequency components while suppressing noise, and employs interactive convolution blocks to fuse multi-domain features effectively. Extensive experiments across eight benchmark datasets show that TSGformer achieves the best results on five datasets, with an MSE of 0.354 on Exchange, improving upon the best baselisnes by 2.4%. Ablation studies further verify the effectiveness of each proposed component, and visualization analyses reveal that TSGformer captures meaningful dynamic correlations aligned with real-world patterns. Full article

The column photobioreactor has become the predominant approach for carbon sequestration by microalgae in power plant settings, owing to its capacity for high-density cultivation and efficient light energy utilization. Due to the dense arrangement of the columnar photobioreactor and its height, insufficient light became one of the main factors limiting the carbon sequestration rate of microalgae growth. In this paper, a light resource optimization method of reflective baffle and top diffusing glass was proposed. When the angle of reflective baffle on the north and east walls was 35°, and the angle of reflective baffle on the west and south floors was 0°, the overall light radiation intensity of the reactor array became the largest, reaching up to 916.81 W/m², which was 14.39% higher than that before the optimization. The replacement of the top glass with diffusing material converted the direct radiation of solar radiation into scattered radiation. When the transmittance was 95% and the haze was 95%, the overall average light radiation intensity of the algal solution reached 830.93 W/m², which was an increase of 3.7%. Four new exhaust air distribution methods were proposed, in which the three-entrance staggered-arrangement type glasshouse had the lowest algal liquid temperature. Full article

Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease characterized by chronic inflammation, extracellular matrix degradation, and smooth muscle cell apoptosis. Porphyromonas gingivalis (P. gingivalis), a key periodontal pathogen, has been implicated in the progression of cardiovascular diseases, including AAA, but the underlying mechanisms remain unclear. In this study, we investigated the role of GroEL, a bacterial heat shock protein 60 homolog derived from P. gingivalis, in AAA development. We employed a CaCl₂-induced AAA mouse model to evaluate the in vivo effects of GroEL. Mice received periaortic CaCl₂ application followed by intravenous injections of recombinant GroEL. Histological analyses were performed to assess aneurysmal dilation, elastin degradation, and inflammatory cell infiltration. Flow cytometry and immunohistochemistry were used to determine macrophage phenotypes, while cytokine profiles were quantified via ELISA. In vitro, THP-1 monocytes were treated with GroEL to evaluate its impact on macrophage polarization and cytokine expression. Our results showed that GroEL administration significantly enhanced aortic diameter expansion and elastin breakdown, accompanied by increased infiltration of M1-like macrophages and elevated levels of pro-inflammatory cytokines such as TNF-α and IL-6. In vitro findings confirmed that GroEL promotes M1 polarization and inhibits M2 marker expression in THP-1-derived macrophages. These findings suggest that P. gingivalis-derived GroEL plays a pathogenic role in AAA by modulating macrophage polarization toward a pro-inflammatory phenotype. Targeting microbial components such as GroEL may offer new therapeutic strategies for AAA management. Full article

Aims: To investigate the nutritional status and feeding behaviours of nursing home residents and the impact of cognitive impairments and feeding difficulties on nutritional health. Design: A cross-sectional observational design was employed. Methods: The study assessed 51 nursing home residents using the Mini Nutritional Assessment Short-Form (MNA-SF) for nutritional status, the Feeding Difficulty Index (FDI) for mealtime behaviours, and the MoCA (Montreal Cognitive Assessment or The MoCA Test) for cognitive function. Results: The average age of participants was 87.8 years. Nearly half (47.1%) were at high risk of malnutrition, and 13.7% were classified as malnourished. The average MoCA score was 14, indicating moderate cognitive impairment, which was inversely associated with nutritional status. Feeding difficulties were common, as follows: 74.5% of residents paused feeding for over one minute, and 62.8% were distracted during meals. A longer duration of nursing home residency was associated with poorer nutritional outcomes. Overall, 65% of residents required mealtime assistance, with higher FDI scores correlating with greater support needs. Significant positive correlations were found between cognitive function and nutritional status (r = 0.401, p = 0.037) and between food intake and nutritional status (r = 0.392, p = 0.004). In contrast, residency duration (r = −0.292, p = 0.037) and feeding difficulties (r = −0.630, p < 0.001) were negatively associated with MNA-SF scores. FDI scores were strongly associated with the level of assistance required during meals (r = 0.763, p < 0.001). This study highlights the critical need for targeted nutritional assessments and interventions in nursing homes, especially for residents with dementia facing cognitive impairments and feeding difficulties. Enhancing staff training on recognising and addressing eating challenges and risk factors is essential for improving nutritional well-being. Conclusions: The study highlighted the profound impact of cognitive impairments and feeding difficulties on the nutritional health of nursing home residents, indicating a high prevalence of malnutrition and a need for comprehensive mealtime assistance. Full article

Chrysanthemum morifolium Ramat. is an important ornamental plant, holding dual economic value as a medicinal and edible plant. Jinsi Huangju is a popular healthy tea drink prepared from the large and elegant shaped flowers of C. morifolium. However, the suboptimal accumulation of bioactive flavonoids during conventional harvest (full bloom stage) limits its commercial potential. To elucidate the molecular mechanisms governing flavonoid biosynthesis in Jinsi Huangju flowers and identify key genetic regulators for metabolic engineering, we performed integrated metabolomic and transcriptomic analyses of flowers at distinct developmental stages using ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) and RNA-seq. Differential metabolites were screened, and candidate genes were validated via transient transformation assays. Among 2146 identified metabolites, flavonoids were the predominant differential compounds, with accumulation patterns being strongly stage dependent. Thirty-eight flavonoid biosynthetic genes and key transcription factors from the MYB, bHLH, and WD40 families exhibited dynamic expression. The CmMYB8a was confirmed as a positive regulator of flavonoid biosynthesis through transient overexpression. This study deciphers the stage-specific flavonoid accumulation in Jinsi Huangju and identifies CmMYB8a as a pivotal regulatory target. Our findings provide genetic resources for breeding high-flavonoid cultivars via molecular design. Full article

The tomato leafminer (Tuta absoluta), a globally invasive pest, poses a major economic threat to tomato production. Although chemical control remains the primary management method, sustainable alternatives are urgently needed. Sex pheromone communication is critical for moth courtship and mating, with pheromone-binding proteins (PBPs) playing a key role in this process. In this study, we identified a PBP gene, TabsPBP2, from the T. absoluta transcriptome. Real-time quantitative PCR (RT-qPCR) revealed that TabsPBP2 is highly expressed in the antennae, with a strong male-biased expression pattern. Ligand-binding assays demonstrated that TabsPBP2 has the highest affinity for the sex pheromones (3E, 8Z, 11Z)-tetradecatrienyl acetate (TDTA) and (3E, 8Z)-tetradecadienyl acetate (TDDA). It also demonstrated a moderate-to-strong binding affinity to several tomato volatiles, including 2-carene, myrcene, α-pinene, cis-3-hexen-l-ol, methyl salicylate, sabinene, and α-terpinene. Molecular docking suggested that hydrophobic interactions predominantly stabilize the TabsPBP2–ligand complexes, with PHE118, PHE12, LEU90, LEU68, and ALA73 identified as key interacting residues. Electroantennogram (EAG) and Y-tube olfactometer assays confirmed that TDTA and TDDA act as strong attractants for male T. absoluta. This study enhances our understanding of the pheromone recognition in T. absoluta and provides a foundation for developing novel, pheromone-based pest control strategies. Full article

Articular cartilage (AC) has a very limited capacity for self-healing once damaged. Chondrocytes maintain AC homeostasis and are key cells in AC tissue engineering (ACTE). However, chondrocytes lose their function due to oxidative stress. Umbilical cord mesenchymal stem cells (UCMSCs) are investigated as an alternative cell source for ACTE. MSCs are known to regulate tissue regeneration through host cell modulation, largely via extracellular vesicle (EV)-mediated cell-to-cell communication. The purpose of this study was to verify whether UCMSC-derived EVs (UCMSC-EVs) enhance chondrocyte function. The mean particle sizes of the UCMSC-EVs were 79.8 ± 19.05 nm. Transmission electron microscopy (TEM) revealed that UCMSC-EVs exhibited a spherical morphology. The presence of CD9, CD63, and CD81 confirmed the identity of UCMSC-EVs, with α-tubulin undetected. UCMSC-EVs maintained chondrocyte survival, and increased chondrocyte proliferation after intake by chondrocytes. UCMSC-EVs upregulated mRNA levels of SOX-9, collagen type II (Col-II), and Aggrecan, while decreasing collagen type I (Col-I) levels. UCMSC-EVs reduced the oxidative stress of chondrocytes by reducing mitochondrial superoxide production and increasing protein levels of SOD-2 and Sirt-3 in chondrocytes. The 50 most abundant known microRNAs (miRNAs) derived from UCMSC-EVs were selected for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. GO analysis revealed enrichment in pathways associated with small GTPase-mediated signal transduction, GTPase regulatory activity, and mitochondrial matrix. The KEGG analysis indicated that these miRNAs may regulate chondrocyte function through the PI3K-Akt, MAPK, and cAMP signaling pathways. In summary, this study shows that UCMSC-EVs enhance chondrocyte function and may be applied to ACTE. Full article

Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third parties, forming a global supply chain model. At the same time, this model produces unpredictable and catastrophic issues, threatening the security of individuals and countries. As for guaranteeing the security of ultra-highly integrated chips, detecting slight abnormalities caused by malicious behavior in the current and voltage is challenging, as is achieving computability within a reasonable time and obtaining a golden reference chip; however, artificial intelligence can make everything possible. For the first time, this paper presents a systematic review of artificial-intelligence-based integrated circuit security approaches, focusing on the latest attack and defense strategies. First, the security threats of integrated circuits are analyzed. For one of several key threats to integrated circuits, hardware Trojans, existing attack models are divided into several categories and discussed in detail. Then, for summarizing and comparing the numerous existing artificial-intelligence-based defense strategies, traditional and advanced artificial-intelligence-based approaches are listed. Finally, open issues on artificial-intelligence-based integrated circuit security are discussed from three perspectives: in-depth exploration of hardware Trojans, combination of artificial intelligence, and security strategies involving the entire life cycle. Based on the rapid development of artificial intelligence and the initial successful combination with integrated circuit security, this paper offers a glimpse into their intriguing intersection, aiming to draw greater attention to these issues. Full article

Groundwater is an important factor for the stability of the subway station pit constructed in the offshore area. To reflect the effects of groundwater drawdown on the stability of the station pit, this work uses a surface settlement formula based on Rayleigh distribution to construct a continuous deformation velocity field based on Terzaghi’s mechanism, so as to derive a theoretical calculation method for the safety factor of the deep station pit anti-uplift considering the effect of seepage force. Taking the seepage force as an external load acting on the soil skeleton, a simplified calculation method is proposed to describe the variation in shear strength with depth. Substituting the external work rate induced by self-weight, surface surcharge, seepage force, and plastic shear energy into the energy equilibrium equation, an explicit expression of the safety factor of the station pit is obtained. According to the parameter study and engineering application analysis, the validity and applicability of the proposed procedure are discussed. The parameter study indicated that deep excavation pits are significantly affected by construction drawdown and seepage force; the presence of seepage, to some extent, reduces the anti-uplift stability of the station pit. The calculation method in this work helps to compensate for the shortcomings of existing methods and has a higher accuracy in predicting the safety and stability of station pits under seepage situations. Full article

Background/Objectives: Iron deficiency without anemia (IDWA) is common among female patients with chronic kidney disease (CKD), yet the clinical implications of iron therapy in this population remain uncertain. While iron supplementation is frequently used in anemic CKD patients, evidence regarding its outcomes in non-anemic, iron-deficient individuals is limited and conflicting. Methods: This retrospective cohort study utilized the multi-institutional TriNetX database to examine the 5-year outcomes of iron therapy in adult women with stage 3 CKD, normal hemoglobin (≥12 g/dL), normal mean corpuscular volume (MCV), and low serum ferritin (<100 ng/mL). Primary outcomes included all-cause mortality, major adverse cardiovascular events (MACE), acute kidney injury (AKI), pneumonia, progression to advanced CKD (estimated glomerular filtration rate ≤30 mL/min/1.73 m²), and gastrointestinal (GI) bleeding. Results: We identified 53,769 eligible non-anemic patients with stage 3 CKD, low serum ferritin levels, and normal MCV. Propensity score matching (1:1) was conducted on demographic variables to compare iron-treated (n = 6638) and untreated (n = 6638) cohorts. Over the 5-year follow-up, iron therapy in non-anemic females with stage 3 CKD, low ferritin levels, and iron supplementation was significantly associated with increased risks of MACE, AKI, pneumonia, CKD progression, and GI bleeding (log-rank p < 0.0001). No significant difference in all-cause mortality was observed. Data on transferrin saturation and the dosage of iron supplementation were unavailable. Conclusions: In non-anemic women with stage 3 CKD and low ferritin levels, iron supplementation was linked to increased MACE, renal, and pneumonia risks without evident survival benefits. These findings suggest that iron therapy in this group of patients may not confer cardiovascular benefit and may pose risks. Full article

Background: Exercise-induced fatigue arises primarily from energy substrate depletion and the accumulation of metabolites such as lactate and ammonia, which impair performance and delay recovery. Emerging evidence implicates gut microbiota modulation—particularly via probiotics—as a means to optimize host energy metabolism and accelerate clearance of fatigue-associated by-products. Objective: This study aimed to determine whether live or heat-inactivated Lacticaseibacillus paracasei NB23 can enhance exercise endurance and attenuate fatigue biomarkers in a murine model. Methods: Forty male Institute of Cancer Research (ICR) mice were randomized into four groups (n = 10 each) receiving daily gavage for six weeks with vehicle, heat-killed NB23 (3 × 10¹⁰ cells/human/day), low-dose live NB23 (1 × 10¹⁰ CFUs/human/day), or high-dose live NB23 (3 × 10¹⁰ CFUs/human/day). Forelimb grip strength and weight-loaded swim-to-exhaustion tests assessed performance. Blood was collected post-exercise to measure serum lactate, ammonia, blood urea nitrogen (BUN), and creatine kinase (CK). Liver and muscle glycogen content was also quantified, and safety was confirmed by clinical-chemistry panels and histological examination. Results: NB23 treatment produced dose-dependent improvements in grip strength (p < 0.01) and swim endurance (p < 0.001). All NB23 groups exhibited significant reductions in post-exercise lactate (p < 0.0001), ammonia (p < 0.001), BUN (p < 0.001), and CK (p < 0.0001). Hepatic and muscle glycogen stores rose by 41–59% and 65–142%, respectively (p < 0.001). No changes in food or water intake, serum clinical-chemistry parameters, or tissue histology were observed. Conclusions: Our findings suggest that both live and heat-treated L. paracasei NB23 may contribute to improved endurance performance, increased energy reserves, and faster clearance of fatigue-related metabolites in our experimental model. However, these results should be interpreted cautiously given the exploratory nature and limitations of our study. Full article

Obtaining the echo of individual fish is an important prerequisite for fisheries acoustic applications, such as in situ measurement of fish target strength and assessment of fish abundance using the counting method. It is also the foundation for evaluating the growth status of farmed fish and managing aquaculture risks. The density of farmed fish populations is typically higher, and such high-density aquaculture further increases the difficulty of obtaining individual fish echoes in practical applications. Building upon previous research and considering the behavioral characteristics of fish in aquaculture settings, this study conducted performance simulations, live fish experiments in simulated aquaculture cages, and comparative evaluations of three individual fish broadband echo detection methods based on a broadband signal system: the amplitude pulse width method (APM) based on echo envelopes, the peak detection and time delay estimation method (PDM), and the peak time delay combined with instantaneous frequency method (PDIM). This study assumed a dorsolateral fish orientation, which limits its research scope and applicability. The results showed that the PDIM achieved a detection accuracy of 78.34% and a false recognition rate of 1.32%. The APM based on echo envelopes was insensitive to individual fish echoes and had lower recognition accuracy. The PDM exhibited better individual fish echo capture capabilities, while the PDIM demonstrated superior overlapping echo rejection capabilities. Full article

Background/Objective: Staphylococcus aureus (S. aureus) is a clinically significant pathogenic bacterium. Daptomycin (DAP) is a cyclic lipopeptide antibiotic used to treat infections caused by multidrug-resistant Gram-positive bacteria, including S. aureus. However, DAP currently faces clinical limitations due to its short half-life, toxic side effects, and increasingly severe drug resistance issues. This study aimed to develop a biomimetic nano-drug delivery system to enhance targeting ability, prolong blood circulation, and mitigate resistance of DAP. Methods: DAP-loaded chitosan nanocomposite particles (DAP-CS) were prepared by electrostatic self-assembly. Macrophage membrane vesicles (MM) were prepared by fusion of M1-type macrophage membranes with 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). A biomimetic nano-drug delivery system (DAP-CS@MM) was constructed by the coextrusion process of DAP-CS and MM. Key physicochemical parameters, including particle diameter, zeta potential, encapsulation efficiency, and membrane protein retention, were systematically characterized. In vitro immune escape studies and in vivo zebrafish infection models were employed to assess the ability of immune escape and antibacterial performance, respectively. Results: The particle size of DAP-CS@MM was 110.9 ± 13.72 nm, with zeta potential +11.90 ± 1.90 mV, and encapsulation efficiency 70.43 ± 1.29%. DAP-CS@MM retained macrophage membrane proteins, including functional TLR2 receptors. In vitro immune escape assays, DAP-CS@MM demonstrated significantly enhanced immune escape compared with DAP-CS (p < 0.05). In the zebrafish infection model, DAP-CS@MM showed superior antibacterial efficacy over both DAP and DAP-CS (p < 0.05). Conclusions: The DAP-CS@MM biomimetic nano-drug delivery system exhibits excellent immune evasion and antibacterial performance, offering a novel strategy to overcome the clinical limitations of DAP. Full article

In the field of interferometric fiber-optic sensing, the phase-shifting technique is well known as a highly efficient method for retrieving the phase signal from the interference light intensity. The rectangular-pulse binary phase modulation (RPBPM) method is a typical phase-shifting method with the advantages of high efficiency, low complexity, and easy array multiplexing. Exploring the impact of the parameters on the performance is of great significance for guiding its application in practical systems. In this study, the influence of the sampling interval and modulation depth deviation involved in the method is analyzed in detail. Through a comparative simulation analysis with the traditional heterodyne and phase-generated carrier methods, the superiority of the RPBPM method is effectively validated. Meanwhile, an improved method based on the ellipse fitting of the Lissajous figure is proposed to compensate for the error and improve the signal-to-noise-and-distortion ratio (SINAD) from 26.3 dB to 37.1 dB in a specific experiment. Finally, the experimental results guided by the above method show excellent performance in a practical vibration system. Full article