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Robust text detection in foggy traffic scenes using an enhanced CTPN model with de-fogging pre-processing
A comparative study on life cycle assessment and economic analysis of photovoltaic-based air heating systems based on machine learning prediction
Naringenin-loaded nanoparticles ameliorate scopolamine-induced neurotoxicity
Resveratrol inhibits pancreatic cancer progression via the ING5 signaling pathway
Finite element analysis of stress distributions in knee ligaments and menisci during the Taekwondo Roundhouse Kick
Influence of endodontic access cavity design on root canal localization in mandibular first premolars using microscope and ultrasonic tips
Optical, luminescence and magnetic properties of braunite‒rhodonite nanocomposites synthesized by green aqueous sol‒gel route
Abstract Braunite (Mn 7 SiO 12 )‒rhodonite (MnSiO 3 ) nanocomposites have been synthesized utilizing a green aqueous citrate sol‒gel route. The influence of heat-treatment temperature on the structure and properties of these nanocomposites was investigated. X-ray diffraction and high resolution transmission electron microscopy analyses demonstrated that well-crystallized nanoparticles, having average sizes in the range of 18‒42 nm, were produced. MnSiO 3 -content increased in the nanocomposites with increasing calcination temperature from 600 to 900 °C. Optical, photoluminescence and magnetic properties were determined. Ultraviolet–visible-near infrared diffuse reflectance spectra were used, applying Kubelka–Munk function, for optical absorbance calculation and determination of the band gap energy (E g ). Optical absorption spectra exhibited bands at 415‒438 nm originated from Mn 2+ ions, and other bands at 550 and 599 nm due to absorption of Mn 3+ ions. E g was found to increase with increasing MnSiO 3 -content in the nanocomposites. The obtained nanocomposites gave green fluorescence emissions at 525‒565 nm, a yellow emission at 584 nm and red emissions at 619 nm. All the synthesized nanocomposites exhibited antiferromagnetic properties in which the paramagnetic contribution and magnetization increased as the MnSiO 3 -content increased. The present nanocomposites are promising candidates for application as light emitting diodes as well as magnetoelectronic materials which are used in biomedical applications.
An adaptive multi-scale lightweight network for long-distance small traffic sign detection
Abstract Autonomous driving systems critically rely on the precise detection of distant, small traffic signs to ensure safe and efficient navigation. Nonetheless, existing detection algorithms are confronted with several significant challenges, including the limited efficacy in capturing the subtle visual features of small targets, the adverse effects of complex background clutter, and the imperative for real-time inference via computationally lightweight models. To address these challenges, we propose YOLO-AML, which effectively reduces computational complexity through parameter-free spatial transformations and low-channel convolution operations while preserving fine-grained features of small objects. The proposed Normalization-based Attention with sigmoid and tanh (NAST) module employs a hybrid gating mechanism to precisely regulate attention weight distribution, thereby suppressing background noise without introducing additional convolutional overhead. Furthermore, the C2PSA-LSKA (CLSKA) module integrated into the backbone network enhances the receptive field while minimizing parameter count, effectively mitigating the issue of traffic signs being obscured by background clutter. Additionally, a Normalized Wasserstein Distance (NWD) loss function is introduced to alleviate gradient vanishing commonly encountered with extremely small objects. Experimental results indicate that the optimized model reduces the total number of parameters by 17%, computational complexity by 16.8%, achieves a detection speed of 72.2 FPS, and improves detection accuracy by 2.0%. Grad-CAM heatmap visualization further confirms the model’s enhanced feature discriminability and robustness against background interference. Overall, YOLO-AML demonstrates significant improvements in detection performance under complex real-world driving scenarios.
Computational screening of AI-derived cyclotides as putative VEGFR2 binders for wound-site angiogenesis
Change in diurnal temperature range on the Tibetan plateau in the last 40 years and its influencing factors
Implementation of a multifactorial fall intervention model to guide hospital nurses: A quasi-experimental before-and-after study
Comparable restimulation of human T cells activated with CD3/CD28 beads versus soluble antibody complexes
Natural genetic variation impacts complement inhibitory activity of PFam54 orthologs of Asian Borrelia bavariensis
Abstract European and Asian populations of Borrelia (B.) bavariensis , a causative agent of Lyme borreliosis, substantially differ in their infection dynamics. This is argued to be a byproduct of the unique demographic history of B. bavariensis in relation to colonizing Europe from a highly diverse, ancestral Asian population. Whether genetic factors related to human disease could be unique traits associated with the demographic history of the European population though remains largely unclear. European B. bavariensis possesses at least two anti-complement determinants, BGA66 and BGA71 encoding by genes of the PFam54 gene array. In Asian B. bavariensis populations, the composition of this gene array is highly diverse. To assess functional integrity of PFam54 orthologs, two Asian B. bavariensis isolates, NT24 and JHM1114, were investigated. Despite the substantial observed genetic diversity, the complement-inhibitory and cell-protective function of BGA66 and BGA71 orthologs are largely conserved among European and Asian populations. We also identified two novel PFam54 orthologs of Asian origin, BGA67b and BGA71b, both of which display anti-complement activity on the terminal pathway and confer serum resistance. Taken together, our findings highlight the importance of studying natural variation of proteins potentially involved in immune escape, pathogenesis, and host adaptation.
Simulation of water-mud-inrush in fault fracture zone of deep and long railway tunnel in mountain area
Inulin and multispecies probiotic effects on blood, liver and kidney biochemistry and metabolic and stress-related gene expression in pigs
Abstract Dietary supplementation with probiotics, prebiotics, and their combination (synbiotics) can improve pig health through direct and indirect mechanisms. This study evaluated the effects of probiotics, inulin, and their combination on: (1) blood biochemistry parameters reflecting lipid metabolism, liver function, oxidative stress, and immune status; (2) liver and kidney gene expression and biochemical markers related to energy and reactive oxygen species metabolism; and (3) mineral profiles in blood plasma, liver, and kidneys, including renal aquaporin gene expression. Inulin increased total protein, while raising total and LDL-cholesterol but lowering hepatic cholesterol and triglyceride levels, and upregulating apolipoprotein A1 expression. Probiotics lowered AST and ALT activity and enhanced the expression of energy metabolism genes in the liver and kidneys, similarly to the combined treatment. Inulin increased plasma sodium and phosphorus but reduced liver magnesium and copper contents; probiotics elevated selenium, iron, and phosphorus concentrations in the blood and kidneys. Both supplements improved antioxidant capacity and anti-inflammatory responses, although their combination unexpectedly elevated renal interleukin-6 expression. Overall, probiotics, inulin, and their combination positively affected lipid metabolism, liver function, oxidative balance, and immune status, supporting their potential as natural alternatives to antibiotics in pig nutrition.
Adaptive optimization of the trade-off parameter in acoustic-contrast-control-pressure-matching for personal audio zones using genetic algorithms
Contribution of tissue clearing and 3D image analysis to in vitro modeling of human cortical development
Bacteria-soil–plant linkages underlie the mosaic structure of the soil bacterial communities in near-natural stands of Białowieża Primeval Forest
Abstract Primary temperate forests serve as a natural framework for studying linkages between vegetation, soil properties and microbial communities under minimal human disturbance. Here, we characterize how soil bacterial communities and functional potential vary across five dominant forest types of the Białowieża National Park, representing a natural mosaic of vegetation and edaphic conditions. Using full-length 16S rRNA Oxford Nanopore sequencing, functional profiling via BIOLOG EcoPlates, and applying multivariate analyses, we detected clear differences in bacterial composition and carbon-substrate utilization profile among forest types. Distance-based redundancy analysis (dbRDA) identified soil pH as the primary abiotic gradient shaping bacterial communities, while RLQ, fourth-corner and multiblock sPLS analyses consistently supported bacteria-soil-vegetation linkages. Three consistent ecological clusters emerged across the forest mosaic. Coniferous forests with acidophilic bacterial assemblages linked to strongly acidic soils and ericaceous understoreys, broadleaf forests with bacterial genera associated with moderately acidic, nutrient-depleted soils and shade-tolerant vegetation, and alder forests characterized by richer, more metabolically active microbial communities occurring in less acidic soils with tall-herb understoreys. Mixed forests displayed broad internal variability, reflecting their wide range of vegetation and soil conditions. Overall, environmental filtering structures distinct bacterial communities of this primary temperate forest, providing a valuable baseline for future plant-soil-microbiome studies.