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In this paper, two three-node triangular thin plate/shell elements are proposed based on the absolute nodal coordinate formulation. As the gradient deficient element, the thin plate/shell element does not possess a full Jacobian matrix for the mapping between different configurations. Thus, the formulation cannot be derived in the conventional method directly based on the continuum mechanics. The independent area coordinate gradients with obvious geometrical interpretation are introduced to simplify the derivation of the shape function. To account for the initially curved reference configuration, the curvilinear coordinate system is used as the global structure coordinate system to calculate the Green-Lagrange strain and formulate the elastic force. The tangent plane is built node-wise to transform the global curvilinear structural gradients to the local area gradients. In this way, the problem of the slope discontinuity associated with the area gradient is circumvented and the continuity of the structural gradient is guaranteed by the standard element assembly procedure. The generalized transformation between the vectors of the Bézier triangle control points and the nodal vectors of the triangular element is presented. Thus, the elements can be used for the integration of computer-aided design and analysis. Finally, the accuracy and convergence property of the new ANCF triangular plate/shell elements are verified by both static and dynamic numerical examples.

Freeze–thaw cycles in soil are driven by water migration, phase transitions, and heat transfer, which themselves are closely coupled variables in the natural environment. To simulate this complex periglacial process at different time and length scales, a multi-physics model was established by solving sets of equations describing fluid flow and heat transfer, and a dynamic equilibrium equation for phase changes in moisture. This model considers the effects of water–ice phase changes on the hydraulic and thermal properties of soil and the effect of latent heat during phase transition. These equations were then discretized by using the finite volume method and solved using iteration. The open-source software OpenFOAM was used to generate computational code for simulation of coupled heat and fluid transport during freezing and thawing of soil. A set of laboratory freezing tests considering two thermal boundary conditions were carried out, of which the results were obtained to verify the proposed model. In general, the numerical solutions agree well with the measured data. A railway embankment problem, incorporating soil hydrothermal behavior in response to seasonal variations in surface temperature, was finally solved with the finite volume-based approach, indicating the algorithm’s robustness and flexibility.

We have developed a novel deconvolution‐based reverse time migration method to image lithospheric structures using teleseismic data recorded by dense seismic arrays. Unlike traditional approaches that rely on the retrieval of Green's functions (or receiver functions), the new method directly utilizes the recorded three‐component (3‐C) seismic waveforms to reconstruct subsurface wavefields, which has the advantage of avoiding the estimation and removal of source time function. Importantly, it enables the asymptotic estimation of P‐to‐S transmission conversion coefficients at the elastic discontinuities and enhances resolving power for the fine‐scale heterogeneities. Taking these improvements, we have obtained a full three‐dimensional (3‐D) high‐resolution image of the subduction zone beneath southwest Japan. This image provides a comprehensive configuration of the severely deformed subducting plate beneath the Kii Channel and Kinki Peninsula. Plain Language Summary Wave equations based seismic imaging method theoretically possesses the most effective capacity for characterizing crustal and upper mantle strong laterally heterogeneous structures. However, its advantages have not been well manifested in the imaging of lithospheric structures, primarily due to the uncertainties introduced by the laborious data preprocessing to remove the complex source‐side effects associated with each earthquake event. To address these uncertainties, we propose a novel method to automatically eliminate source side effects by introducing a deconvolution imaging condition. This enables the direct use of three‐component seismic records only requiring some fundamental preprocessing, such as retrending, remeaning, tapering, and band‐pass filtering, to image the Earth's interior structures. Accordingly, the first attempt of full three‐dimensional elastic imaging beneath southwest Japan is intriguing, and unveils more detailed structures of the subduction zones compared to previous studies. Key Points Deconvolution imaging condition is proposed for elastic reverse‐time migration of teleseismic waveforms with minimal data preconditioning Complex influence of source time function and long‐distance propagation of the incident wavefield is effectively handled Three‐dimensional elastic reverse time migration image beneath southwest Japan reveals more detailed structures of the Philipine Sea plate

Background Methyl jasmonate (MeJA), which has been identified as a lipid-derived stress hormone, mediates plant resistance to biotic/abiotic stress. Understanding MeJA-induced plant defense provides insight into how they responding to environmental stimuli. Result In this work, the dynamic network analysis method was used to quantitatively identify the tipping point of growth-to-defense transition and detect the associated genes. As a result, 146 genes were detected as dynamic network biomarker (DNB) members and the critical defense transition was identified based on dense time-series RNA-seq data of MeJA-treated Arabidopsis thaliana . The GO functional analysis showed that these DNB genes were significantly enriched in defense terms. The network analysis between DNB genes and differentially expressed genes showed that the hub genes including SYP121, SYP122, WRKY33 and MPK11 play a vital role in plant growth-to-defense transition. Conclusions Based on the dynamic network analysis of MeJA-induced plant resistance, we provide an important guideline for understanding the growth-to-defense transition of plants’ response to environment stimuli. This study also provides a database with the key genes of plant defense induced by MeJA.

The automatic 3D reconstruction of indoor scenes is of great significance in the application of 3D-scene understanding. The existing methods have poor resilience to the incomplete and noisy point cloud, which leads to low-quality results and tedious post-processing. Therefore, the objective of this work is to automatically reconstruct indoor scenes from an incomplete and noisy point-cloud base on semantics and primitives. In this paper, we propose a semantics-and-primitives-guided indoor 3D reconstruction method. Firstly, a local, fully connected graph neural network is designed for semantic segmentation. Secondly, based on the enumerable features of indoor scenes, a primitive-based reconstruction method is proposed, which retrieves the most similar model in a 3D-ESF indoor model library by using ESF descriptors and semantic labels. Finally, a coarse-to-fine registration method is proposed to register the model into the scene. The results indicate that our method can achieve high-quality results while remaining better resilience to the incompleteness and noise of point cloud. It is concluded that the proposed method is practical and is able to automatically reconstruct the indoor scene from the point cloud with incompleteness and noise.

Water-soluble fluorescent carbon dots (CDs) were synthesized by a hydrothermal method using citric acid as the carbon source and ethylenediamine as the nitrogen source. The repeated and scale-up synthetic experiments were carried out to explore the feasibility of macroscopic preparation of CDs. The CDs/Fe3+ composite was prepared by the interaction of the CDs solution and Fe3+ solution. The optical properties, pH dependence and stability behavior of CDs or the CDs/Fe3+ composite were studied by ultraviolet spectroscopy and fluorescence spectroscopy. Following the principles of fluorescence quenching after the addition of Fe3+ and then the fluorescence recovery after the addition of asorbic acid, the fluorescence intensity of the carbon dots was measured at λex = 360 nm, λem = 460 nm. The content of ascorbic acid was calculated by quantitative analysis of the changing fluorescence intensity. The CDs/Fe3+ composite was applied to the determination of different active molecules, and it was found that the composite had specific recognition of ascorbic acid and showed an excellent linear relationship in 5.0–350.0 μmol·L−1. Moreover, the detection limit was 3.11 μmol·L−1. Satisfactory results were achieved when the method was applied to the ascorbic acid determination in jujube fruit. The fluorescent carbon dots composites prepared in this study may have broad application prospects in a rapid, sensitive and trace determination of ascorbic acid content during food processing.

With the advancement of intelligent campus data acquisition technology, student behavioral data are growing in size, variety, and real-time throughput, posing challenges to the storage capacity and computing power of traditional behavioral data analysis methods. The study focuses on the application of association rule mining in student behavioral data analysis. Data collection, storage, computation, and analysis all comprise integral parts of a four-layer data association mining architecture, and the three-step mining process from “data preprocessing” to “finding association rules” to “acquiring relevant knowledge” is described. The existing mining algorithm is updated to address the issues of overscanning of the original dataset and excess iterations. The findings from the case study reveal that the number of iterations in the modified mining algorithm is greatly lessened, effectively improving the mining efficiency of the massive student behavioral dataset.

Background Bacillus subtilis spores have been commonly used for the surface display of various food-related or human antigens or enzymes. For successful display, the target protein needs to be fused with an anchor protein. The preferred anchored proteins are the outer-coat proteins of spores; outer-coat proteins G (CotG) and C (CotC) are commonly used. In this study, mutant trehalose synthase (V407M/K490L/R680E TreS) was displayed on the surface of B. subtilis WB800n spores using CotG and CotC individually or in combination as an anchoring protein. Results Western blotting, immunofluorescence, dot blot, and enzymatic-activity assays detected TreS on the spore surface. The TreS activity with CotC and CotG together as the anchor protein was greater than the sum of the enzymatic activities with CotC or CotG alone. The TreS displayed on the spore surface with CotC and CotG together as the anchoring protein showed elevated and stable specific activity. To ensure spore stability and prevent spore germination in the trehalose preparation system, two germination-specific lytic genes, sleB and cwlJ , were deleted from the B. subtilis WB800n genome. It was demonstrated that this deletion did not affect the growth and spore formation of B. subtilis WB800n but strongly inhibited germination of the spores during transformation. The conversion rate of trehalose from 300 g/L maltose by B. subtilis strain WB800n( ΔsleB , ΔcwlJ )/ cotC - treS – cotG - treS was 74.1% at 12 h (350 U/[g maltose]), and its enzymatic activity was largely retained, with a conversion rate of 73% after four cycles. Conclusions The spore surface display system based on food-grade B. subtilis with CotC and CotG as a combined carrier appears to be a powerful technology for TreS expression, which may be used for the biotransformation of d -maltose into d -trehalose.

Accurately predicting short-term congestions in ship traffic flow is important for water traffic safety and intelligent shipping. We propose a method for predicting the traffic flow of ships by applying the whale optimization algorithm to an extreme learning machine. The method considers external environmental uncertainty and complexity of ships navigating in traffic-intensive waters. First, the parameters of ship traffic flow are divided into multiple modal components using variational mode decomposition and extreme learning machine. The machine and the whale optimization algorithm constitute a hybrid modelling approach for predicting individual modal components and integrating the results of individual components. Considering a map between ship traffic flow parameters and congestion, fuzzy c-means clustering is used to predict the level of ship traffic congestion. To verify the effectiveness of the proposed method, ship traffic flow data of the Yangtze River estuary were selected for evaluation. Results from the proposed method for predicting ship traffic flow parameters are consistent with measurements. Specifically, the prediction accuracy of the ship traffic congestion reaches 76.04%, which is reasonable and practical for predicting ship traffic congestion.

Background: Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with late diagnosis; therefore, the identification of new early biomarkers could help reduce mortality. Efferocytosis, a process in which one cell engulfs another cell, including macrophages, dendritic cells, NK cells, etc., plays a complex role in tumorigenesis, sometimes promoting and sometimes inhibiting tumor development. However, the role of efferocytosis-related genes (ERGs) in HCC progression has been poorly studied, and their regulatory effects in HCC immunotherapy and drug targeting have not been reported. Methods: We downloaded efferocytosis-related genes from the Genecards database and screened for ERGs that showed significant expression changes between HCC and normal tissues and were associated with HCC prognosis. Machine learning algorithms were used to study prognostic gene features. CIBERSORT and pRRophetic R packages were used to evaluate the immune environment of HCC subtypes and predict treatment response. CCK-8 experiments conducted on HCC cells were used to assess the reliability of drug sensitivity prediction. Results: We constructed a prognostic prediction model composed of six genes, and the ROC curve showed good predictive accuracy of the risk model. In addition, two ERG-related subgroups in HCC showed significant differences in tumor immune landscape, immune response, and prognostic stratification. The CCK-8 experiment conducted on HCC cells confirmed the reliability of drug sensitivity prediction. Conclusion: Our study emphasizes the importance of efferocytosis in HCC progression. The risk model based on efferocytosis-related genes developed in our study provides a novel precision medicine approach for HCC patients, allowing clinicians to customize treatment plans based on unique patient characteristics. The results of our investigation carry noteworthy implications for the development of individualized treatment approaches involving immunotherapy and chemotherapy, thereby potentially facilitating the realization of personalized and more efficacious therapeutic interventions for HCC.