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Valorization of novel bifunctional waterborne coatings with UV irradiation resistance and antimicrobial activity
Abstract This research aimed to create bifunctional acrylic waterborne coatings capable of absorbing UV radiation and resisting microbial growth. The compound 4-[2(3-acetylphenyl) diazenyl]-3,5-dimethylphenol (ADD) was incorporated into the waterborne acrylic resin at concentrations of 0.1%, 0.25%, and 0.5%. The coatings underwent characterization through scanning electron microscopy (SEM), mechanical property testing, and the CIELab color method after 500 h of UV exposure to assess their UV shielding effectiveness. Furthermore, the antimicrobial properties of both ADD powder and the coatings were evaluated against Gram-negative bacteria (Helicobacter pylori), Gram-positive bacteria (Staphylococcus aureus), and pathogenic fungi (Candida albicans) using the disc diffusion method. Results indicated that the coatings with 0.25% and 0.5% ADD retained their integrity, showing no cracks or color and texture changes after UV exposure. In contrast, the 0.1% ADD coating exhibited significant alterations in the a* value, revealing its susceptibility to UV damage and limited UV absorption. Positive a* values confirmed the red tint of the films. Antimicrobial activity was notable, with inhibition zones measuring 14 to 26 mm against Staphylococcus aureus, 11 to 21 mm against Helicobacter pylori, and 12 to 20 mm against Candida albicans. Overall, this study demonstrated that the developed coatings with ADD significantly enhance UV absorption and exhibit promising antimicrobial properties, effectively overcoming the limitations of existing commercial coatings and offering a viable solution for protecting surfaces from UV radiation and microbial contamination.
Immune-coagulation dynamics in severe COVID-19 revealed by autoantibody profiling and multi-omics integration
Abstract Severe COVID-19 is characterized by immune-coagulation dysregulation, yet the contribution of related autoantibodies remains poorly understood. We investigated relationships between plasma autoantibody reactivities, whole-blood transcriptomics, plasma proteomics, and clinical laboratory parameters in a cohort of hospitalized COVID-19 patients. Transcriptomic analysis revealed that 42 curated coagulation and complement cascade genes were upregulated in severe cases compared to healthy controls, with 15 genes, including CR1L, ELANE, ITGA2B, ITGB3, VWF, TFPI, PROS1, MMRN1, and SELP (> 1.2 log2 fold-change), also significantly different from mild cases. Autoantibody profiling against eight coagulation-related proteins (ADAMTS13, Factor V, Protein S, SERPINC1, Apo-H, PROC1, Prothrombin, and PF4) showed reactivities below positivity thresholds across all groups. Using an exploratory approach, in severe cases, subthreshold autoantibody candidates (FDR < 0.25) showed negative correlation trends with select gene expressions and inflammatory markers (Factor V with IL-6 and CXCL10), suggesting potential disease-specific immunomodulatory associations. In contrast, while mild cases exhibited stronger gene-protein correlations, they showed limited associations with antigen reactivities or clinical laboratory parameters. Additionally, no correlations were observed between autoantibodies and platelet-counts or Fibrin-D-dimer levels. Age-associated increases in antigen reactivities were noted in severe disease, implying a role for immunosenescence. These findings support further investigation into the role of subthreshold autoantibody candidates in thromboinflammatory COVID-19 pathogenesis.
An instance segmentation network for discharging carbon traces inside oil-immersed transformers with boundary and detail features enhancement
Fibro predict a machine learning risk score for advanced liver fibrosis in the general population using Israeli electronic health records
The therapeutic effect of Qishen Huoxue Granule on myocardial injury in sepsis rats and its underlying mechanism via suppressing excessive autophagy
Interspecific competition with the American Xanthium orientale L. as a possible cause of the decline of the Old-World X. strumarium L.
Abstract Xanthium is represented in Europe by three species complexes: X. strumarium L., X. orientale L., and X. spinosum L. The former two complexes are similar, in both morphology and ecological requirements. Xanthium strumarium is native to the Old World, whereas X. orientale originates from America and was accidentally introduced into Europe about two centuries ago. Since then, it has colonized the whole continent, while the native congener has become increasingly rare. Over two years, we conducted competition experiments to assess the impact of the introduced X. orientale on the fitness of the native X. strumarium . Germination time, dry biomass, number of burs (pistillate flower heads) and bur biomass were measured as proxies of fitness. Xanthium strumarium was grown alone (control), together with conspecifics (intraspecific competition) or with X. orientale plants (interspecific competition). We also evaluated the allelopathic effect of X. orientale over X. strumarium , by watering Xanthium seedlings with exudate of X. orientale dry leaves. Growth and reproductive traits of X. strumarium were significantly lower in individuals growing in proximity of X. orientale compared to the control, whereas intraspecific competition has a lower but still significant effect. Xanthium orientale, although, germinates and grows faster than the Old-World congener, and under interspecific competition regime, X. strumarium produces significantly lower biomass, number of burs and bur biomass. Watering with exudates negatively influences the germination and the growth of the two species. We therefore believe that interspecific competition of the introduced congener may be one of the causes explaining the drastic decline of X. strumarium populations in Europe in the past century.
Publisher Correction: Analysis of yield stability and genotype–environment interaction for open-pollinated tomato varieties in the Kashmir Himalaya using the AMMI model
Catalytic epoxidation of linoleic acid derived corn oil via in situ performic acid mechanism
Scheduling allocation in 5G slicing networks utilizing weighted exponential and logarithmic functions to improve QoS
Abstract Offering media-rich services, such as streaming videos, for emergency services requires compliance with reliability standards. The deployment of fifth-generation (5G) networks enables a wide range of services and applications with diverse Quality of Service (QoS) requirements. Supporting heterogeneous performance and migrating vital services to 5G networks pose significant challenges for emergency service providers in maintaining QoS. To address this, schedulers allocate resources to various traffic types in a QoS- and channel state-aware manner. The exponential function scheduling method (EXP RULE) is a well-established approach; however, it requires optimization to reduce packet loss rate and latency. This study proposes the Hybrid Weighted Exponential and Logarithmic Rule (HWEL RULE), which enhances EXP RULE by integrating weighted logarithmic functions to improve QoS metrics in 5G slicing networks. Operating within a Fog Radio Access Network (F-RAN) framework with Network Functions Virtualization (NFV), HWEL RULE dynamically allocates Baseband Unit (BBU) resources to Ultra-Reliable Low-Latency Communications (URLLC), Enhanced Mobile Broadband (eMBB), and Massive Machine-Type Communications (mMTC). Using LTE-Sim simulations, HWEL RULE demonstrates up to a 30.06% reduction in packet loss rate, 21% lower latency for video traffic, 23.5% lower latency for VoIP, 8.6% higher throughput, and 1.2% improved fairness compared to EXP RULE. This incremental enhancement ensures compatibility with existing 5G architectures while significantly improving real-time traffic performance.
The impact of the ratio of renal parenchyma to renal volume on stone-free rates after RIRS: a retrospective study
Repeated laparoscopic Roux-en-Y hepaticojejunostomy techniques and pitfalls to watch out with video
Construction of a prognostic risk model for acute myeloid leukemia based on exosomal genes and analysis of immune microenvironment characteristics
Fatty acid-binding proteins as potential biomarkers for human cancer prognosis
Subtalar joint kinematics defined by a rotational axis translating along the posterior talocalcaneal facet
Abstract The subtalar joint is essential for the normal function of the human foot during bipedal walking, with its kinematics being pivotal for understanding foot biomechanics, disorders, and evolution. Traditionally, the helical axis representation has been used to assess subtalar joint movement, assuming translational motion along the rotational axis. However, recent observations challenge this assumption, revealing predominantly mediolateral translation during walking. To address this discrepancy, we propose a novel method that combines a rotational axis representation with a translational axis aligned parallel to the cylindrical axis of the subtalar joint’s posterior facet. Utilizing human cadaveric lower legs, we quantified subtalar joint motion through CT scan analysis. Comparative evaluations between the conventional helical axis representation and the newly proposed cylindrical axis-based representation revealed a closer correspondence between calcaneus movement and the cylindrical axis, emphasizing the pivotal role of posterior facet morphology in subtalar joint kinematics. This innovative approach provides a more intuitive and clinically useful depiction of subtalar joint biomechanics, potentially leading to deeper insights into fundamental biomechanics and function of the human foot, and improved clinical assessment and treatment strategies for subtalar joint-related pathologies.
Inspiratory muscle weakness further impairs exercise capacity and respiratory functions and increases dyspnea perception in patients with heart failure
Harnessing attention-driven hybrid deep learning with combined feature representation for precise sign language recognition to aid deaf and speech-impaired people
Effect of dendritic structure on the filtration performance of fibrous media during dust loading by CFD-DEM
Condition monitoring and fault diagnosis of power transformer based on non-invasive measurement
Abstract In modern power systems, it is crucial to monitor and detect internal faults in power transformers promptly and accurately to ensure reliability and prevent disruptions. Failure to identify these faults promptly can reduce the transformer’s lifespan, cause system disconnection, and compromise network stability. This paper introduces an innovative method for the discrimination, classification, and localization of internal short-circuit faults in power transformers, with a focus on three types of winding faults: turn-to-turn fault, series short circuits, and shunt short circuits. The proposed method introduces an online detection scheme utilizing the ΔV-Iin locus diagram, which leverages existing measurement devices without requiring additional hardware. A comprehensive winding model was developed in MATLAB to simulate insulation failures, and the method also analyzes the effects of faults and harmonic distortions on transformer performance. Features for fault discrimination and localization are derived from the ΔV-Iin locus and calculated using the practical design specifications of three power transformer models with capacities of 3 MVA, 5 MVA, and 7 MVA, operating at 50 Hz in a three-phase configuration. Experimental results on the 3 MVA transformer demonstrate that the formulated identifier efficiently detected all three types of insulation breakdown with an accuracy of 98.51%. Additionally, the fault localization algorithm achieved a fault location accuracy of approximately 93.28%. The findings indicate that the proposed approach is a robust and reliable tool for assessing the condition of power transformers.