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ObjectiveNegative Poisson’s ratio materials are widely used in various fields because of their unique properties of expansion in tension and contraction in compression.MethodsA honeycomb material with negative Poisson’s ratio was obtained by equal biaxial compression of the two-dimensional Voronoi model, and the effects of different compression ratios on its static tensile/compressive mechanical properties were studied by numerical simulation.ResultsThe results show that the tensile and compressive stress-strain curves of the two-dimensional negative Poisson’s ratio honeycomb prepared by the above method have typical "three-stage" deformation characteristics of porous materials, and show significant tensile and compressive strength asymmetry. Under uniaxial tension, the material shows obvious negative Poisson’s ratio phenomenon. With the increase of compression ratio, the elastic modulus and elastic Poisson’s ratio gradually decrease, and the yield strength and platform stress gradually increase. With the gradual increase of tensile strain, the plastic Poisson’s ratio of the material changes from negative to zero and then to positive. However, due to the mutual contact between the inner edges of the material, the inward deformation of the material is limited. Therefore, the material exhibits positive Poisson’s ratio behavior under uniaxial compression, and its elastic modulus, yield strength, elastic/plastic Poisson’s ratio and platform stress increase with the increase of compression ratio. In addition, the negative Poisson’s ratio material is anisotropic in tension and isotropic in compression.

Self-similar multi-cell structures have been widely applied in engineering fields for their excellent mechanical properties and multi-functional characteristics. In this paper, self-similar inspired multi-cell tubes are constructed by replacing the substructures according to different strategies. The hybrid tubes are built by the space-filling and tessellation of these self-similar inspired multi-cell tubes. The effect of the diameter, layout and hierarchical order are experimentally investigated. The tessellation and space-filling of these multi-cell tubes are numerically and theoretically investigated. The results show that the specific energy absorption (SEA) increases with the hierarchical fractal order. The specific energy absorption of the 2nd order self-similar inspired multi-cell tubes increased by 342.5% and 116.5% compared to the 0th and 1st order multi-cell tubes. It is also found that the increase of the side length is not an effective method to improve the crashworthiness of the lower-order multi-cell tubes. Finally, a theoretical model of the angle element was constructed to predict the mean crushing force of these multi-cell tubes. In general, our research provides an effective method for the design of self-similar inspired multi-cell structures with excellent crashworthiness.

High-quality ontologies are critical to ontology-based applications, such as natural language understanding and information extraction, but logical conflicts naturally occur in the lifecycle of ontology development. To deal with such conflicts, conflict detection and ontology repair become two critical tasks, and we focus on repairing ontologies. Most existing approaches for ontology repair rely on the syntax of axioms or logical consequences but ignore the semantics of axioms. In this paper, we propose an embedding-based approach by considering sentence embeddings of axioms, which translates axioms into semantic vectors and provides facilities to compute semantic similarities among axioms. A threshold-based algorithm and a signature-based algorithm are designed to repair ontologies with the help of detected conflicts and axiom embeddings. In the experiments, our proposed algorithms are compared with existing ones over 20 real-life incoherent ontologies. The threshold-based algorithm with different distance metrics is further evaluated with 10 distinct thresholds and 3 pre-trained models. The experimental results show that the embedding-based algorithms could achieve promising performances.

Schematic knowledge, an important component of knowledge graphs (KGs), defines a rich set of logical axioms based on concepts and relations to support knowledge integration, reasoning, and heterogeneity elimination over KGs. Although several KGs consist of lots of factual knowledge, their schematic knowledge (e.g., subclassOf axioms, disjointWith axioms) is far from complete. Currently, existing KG embedding methods for completing schematic knowledge still suffer from two limitations. Firstly, existing embedding methods designed to encode factual knowledge pay little attention to the completion of schematic knowledge (e.g., axioms). Secondly, several methods try to preserve logical properties of relations for completing schematic knowledge, but they cannot simultaneously preserve the transitivity (e.g., subclassOf) and symmetry (e.g., disjointWith) of axioms well. To solve these issues, we propose a cosine-based embedding method named CosE tailored for completing lightweight schematic knowledge in DL-Litecore. Precisely, the concepts in axioms will be encoded into two semantic spaces defined in CosE. One is called angle-based semantic space, which is employed to preserve the transitivity or symmetry of relations in axioms. The other one is defined as translation-based semantic space that is used to measure the confidence of each axiom. We design two types of score functions for these two semantic spaces, so as to sufficiently learn the vector representations of concepts. Moreover, we propose a novel negative sampling strategy based on the mutual exclusion between subclassOf and disjointWith. In this way, concepts can obtain better vector representations for schematic knowledge completion. We implement our method and verify it on four standard datasets generated by real ontologies. Experiments show that CosE can obtain better results than existing models and keep the logical properties of relations for transitivity and symmetry simultaneously.

In October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies" (https://www.cancer.gov/research/key-initiatives/covid-19/coronavirus-research-initiatives/serological-sciences-network). SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization. To facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology standard reference material and first WHO international standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data. SeroNet institutions reported development of a total of 27 enzyme-linked immunosorbent assay (ELISA) methods, 13 multiplex assays, and 9 neutralization assays and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards. In conclusion, SeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons. IMPORTANCE SeroNet institutions have developed or implemented 61 diverse COVID-19 serological assays and are collaboratively working to harmonize these assays using reference materials to establish standardized reporting units. This will facilitate clinical interpretation of serology results and cross-comparison of research data.

In recent years, fluorine-doped carbon (F–C) materials have attracted widespread attention in the oxygen reduction reaction (ORR) due to their unique performance. However, the strong electron-withdrawing nature of the F element makes metal particles not suitable for the 4e− ORR in proton exchange membrane fuel cells (PEMFCs). In this work, we introduce Zn element to modulate the strong electron-withdrawing effect of F element. At the same time, utilizing the strong polarity of the C–F bond, we construct an electron confinement structure to introduce the concept of potential well in the ORR system for the first time. We prepare the PtZn i-NPs/F-CNT catalyst with a potential well effect to achieve high ORR catalytic efficiency. The catalyst exhibits good ORR performance and corrosion resistance at 80 °C. Furthermore, the PtZn i-NPs/F-CNT cathode assembly reaches a peak power density of 1.49 W cm−2 in the H2/O2 environment and maintains 92.6% of the peak power density after 30 K cycles of accelerated stress testing (AST), with stable operation for 220 hours at a working voltage of 0.67 V. This study offers novel insights into developing efficient and corrosion-resistant ORR electrocatalysts for PEMFCs, serving as a foundation for future development of ORR electrocatalysts in PEMFCs. [ABSTRACT FROM AUTHOR]

Sodium oligomannate (GV-971), an oligosaccharide drug approved in China for treating mild-to-moderate Alzheimer's disease (AD), was previously found to recondition the gut microbiota and limit altered peripheral Th1 immunity in AD transgenic mice. As a follow-up study, we here made advances by pinpointing a Lactobacillus murinus (L.m.) strain that highly expressed a gene encoding a putative adhesin containing Rib repeats (Ribhigh-L.m.) particularly enriched in 5XFAD transgenic mice. Mechanistically, Ribhigh-L.m. adherence to the gut epithelia upregulated fecal metabolites, among which lactate ranked as the top candidate. Excess lactate stimulated the epithelial production of serum amyloid A (SAA) in the gut via the GPR81-NFκB axis, contributing to peripheral Th1 activation. Moreover, GV-971 disrupted the adherence of Ribhigh-L.m. to gut epithelia via direct binding to Rib, which corrected the excess lactate, reduced SAA, and alleviated Th1-skewed inflammation. Together, we gained further insights into the molecular link between gut bacteria and AD progression and the mechanism of GV-971 in treating AD. [ABSTRACT FROM AUTHOR]

Cavitation may occur in water-jet pump during operation of water-jet propulsion vessel, and once cavitation occurs, the tip clearance pulsating pressure of the impeller may be intensified, resulting in increased vibration of the water-jet propulsion unit. In this paper, the cavitation pulsating pressure characteristics at different positions in the pump are studied by experiment and numerical simulation, and the pulsating pressure characteristics in tip clearance are mainly researched. Based on Star-CCM+ commercial software, unsteady Reynolds-averaged Navier-Stokes equations(RANS) numerical simulation is carried out, and the feasibility of the numerical simulation method is verified by uncertainty analysis. The results show that the cavitation pulsating pressure near the leading edge of the impeller in the tip clearance is the largest. The variation of the tip clearance pulsating pressure with the intensification of cavitation is studied by numerical simulation, and its mechanism is revealed. A dimensionless coefficient of net positive suction head (CNPSH) is proposed, and the study shows that the cavitation pulsation pressure coefficients of pumps of different scales are equal when the working conditions are similar and the CNPSH are equal, which indicates that the cavitation pulsating pressure performance of full scale pump can be predicted by model scale. It is of great significance to evaluate the vibration performance of the full scale water-jet propulsion. [ABSTRACT FROM AUTHOR]

Aims: Growing evidence suggests that an imbalanced gut microbiota composition plays a crucial role in the development of neuromyelitis optica spectrum disorders (NMOSD), an inflammatory demyelinating disease primarily affecting the optic nerves and central nervous system (CNS). In light of this, we explored the potential therapeutic benefits of GV‐971 in NMOSD. GV‐971 is a drug used for treating mild‐to‐moderate Alzheimer's disease, which targets the gut‐brain axis and reduces neuroinflammation. Methods: To evaluate GV‐971's effects, we employed the experimental autoimmune encephalomyelitis (EAE) mouse model to establish NMOSD animal models. This was achieved by injecting NMO‐IgG into aged mice (11 months old) or using NMO‐IgG along with complement injection and microbubble‐enhanced low‐frequency ultrasound (MELFUS) techniques in young mice (7 weeks old). We assessed the impact of GV‐971 on incidence rate, clinical scores, body weight, and survival, with methylprednisolone serving as a positive control. In NMOSD models of young mice, we analyzed spinal cord samples through H&E staining, immunohistochemistry, and Luxol Fast Blue staining. Fecal samples collected at different time points underwent 16S rRNA gene sequencing, while plasma samples were analyzed using cytokine array and untargeted metabolomics analysis. Results: Our findings indicated that GV‐971 significantly reduced the incidence of NMOSD, alleviated symptoms, and prolonged survival in NMOSD mouse models. The NMOSD model exhibited substantial neuroinflammation and injury, accompanied by imbalances in gut microbiota, peripheral inflammation, and metabolic disorders, suggesting a potentially vicious cycle that accelerates disease pathogenesis. Notably, GV‐971 effectively reduces neuroinflammation and injury, and restores gut microbiota composition, as well as ameliorates peripheral inflammation and metabolic disorders. Conclusions: GV‐971 attenuates the progression of NMOSD in murine models and reduces neuroinflammation and injury, likely through its effects on remodeling gut microbiota and peripheral inflammation and metabolic disorders. [ABSTRACT FROM AUTHOR]