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Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity 1 – 3 , but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible 4 , 5 . More reversible chemistry can improve crystallinity 6 – 9 , but this typically yields COFs with poor physicochemical stability and limited application scope 5 . Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h −1  g −1 . This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control. A protocol in which monomers are pre-organized using a reversible and removable urea linkage enables the production of covalent organic frameworks with higher crystallinity and porosity than those produced using standard approaches with randomly aligned monomers.

The separation of amino acids from complex mixtures remains an essential yet multi-step, energy-intensive process. Membrane separation technology offers a more energy-efficient alternative, but its effectiveness relies on achieving highly precise molecular recognition. Here, we report a homochiral covalent organic framework (COF) membrane with ordered ultra-microporous pore structures for targeted extraction of specific enantiomer from amino acid mixtures. Benefiting from its high crystallinity and ultra-microporous chiral channels, the membrane exhibits both excellent permeability and enantioselectivity. A combination of experimental results, density functional theory calculations, and molecular dynamics simulations reveal a retarded transport mechanism, wherein stronger interactions between L -enantiomers and the homochiral pores hinder their transmembrane diffusion. We further demonstrate a two-stage cascade membrane process to simultaneously fractionate and enantioseparate amino acid mixtures, achieving near pure (99.5%) D -threonine from an eight-component protein hydrolysis complex. This study offers a promising and sustainable membrane-based solution for efficient amino acid purification. The use of membranes for the separation of complex amino acid mixtures is energy efficient but relies on achieving precise molecular recognition. Here, the authors report on a homochiral covalent organic framework membrane for the enantioseparation and fractionation of amino acids.

The accelerated carbonation, natural carbonation, fast freeze-thaw test, and pore structure analysis of C30 and C50 concrete with different proportions of iron tailings powder and slag powder were tested, respectively. The results show that the accelerated carbonation depth and natural carbonation depth of concrete increase with the increase of iron tailings powder content. The prediction model of carbonation depth of iron tailings powder concrete is established by introducing the iron tailings content coefficient and strength influence coefficient. The error between the calculated value of the model and the test value of 28 d curing concrete natural carbonation depth is small, which proves that the model is completely feasible. When iron tailings powder accounts for 50% of mineral admixture, it is helpful to improve the frost resistance of concrete. According to the pore structure analysis, the introduction of iron tailings powder can optimize the pore structure, improve the porosity of harmless and less harmful pores, and thus improve the frost resistance.

Purpose This study aims to investigate the effect of hotel servicescape on customer citizenship behaviors “CCBs” by addressing customer engagement as a mediator and gender as a moderator. Design/methodology/approach A total of 619 questionnaires were collected from hotel customers. Structural equation modeling was applied for data analysis. Findings Customer engagement mediates the effects of physical and social servicescapes on CCBs of providing feedback to an organization, making recommendations and helping other customers. Moreover, the indirect effects of physical servicescape on the three types of CCBs through customer engagement are stronger for male than for female customers, whereas no significant gender difference is observed in those effects of social servicescape on these types of CCBs through customer engagement. Research limitations/implications This study can help hotels promote the three types of CCBs and customer engagement by creating wonderful physical and social servicescape elements. The major limitation is that this study collected survey data outside the hotel environment. Originality/value This study enriches current knowledge on the servicescape-driven responses by exploring how hotel servicescape elements affect the three types of CCBs through customer engagement. Additionally, the different moderating roles of gender in the indirect influences of servicescape elements on these types of CCBs are presented.

Single-atom catalysts (SACs) have attracted considerable attention in the catalysis community. However, fabricating intrinsically stable SACs on traditional supports (N-doped carbon, metal oxides, etc.) remains a formidable challenge, especially under high-temperature conditions. Here, we report a novel entropy-driven strategy to stabilize Pd single-atom on the high-entropy fluorite oxides (CeZrHfTiLa)O x (HEFO) as the support by a combination of mechanical milling with calcination at 900 °C. Characterization results reveal that single Pd atoms are incorporated into HEFO (Pd 1 @HEFO) sublattice by forming stable Pd–O–M bonds (M = Ce/Zr/La). Compared to the traditional support stabilized catalysts such as Pd@CeO 2 , Pd 1 @HEFO affords the improved reducibility of lattice oxygen and the existence of stable Pd–O–M species, thus exhibiting not only higher low-temperature CO oxidation activity but also outstanding resistance to thermal and hydrothermal degradation. This work therefore exemplifies the superiority of high-entropy materials for the preparation of SACs. Fabricating intrinsically stable single-atom catalysts (SACs) on traditional supports remains a formidable challenge in catalysis. Here, the authors propose a new strategy to construct a sintering-resistant Pd SAC on a novel equimolar high-entropy fluorite oxide.

A refined a priori error analysis of the lowest order (linear) virtual element method (VEM) is developed for approximating a model two-dimensional Poisson problem. A set of new geometric assumptions is proposed on the shape regularity of polygonal meshes. A new universal error equation for the lowest order (linear) VEM is derived for any choice of stabilization, and a new stabilization using a broken 1/2-seminorm is introduced to incorporate short edges naturally into the a priori error analysis on isotropic elements. The error analysis is then extended to a special class of anisotropic elements with high aspect ratio originating from a body-fitted mesh generator, which uses straight lines to cut a shape regular background mesh. Lastly, some commonly used tools for triangular elements are revisited for polygonal elements to give an in-depth view of these estimates' dependence on shapes.

Remote sensing image segmentation is a vital method in image analysis that significantly contributes to the extraction of surface information and aids in land use planning. This study utilizes the LoveDA dataset to investigate the segmentation performance of three classic deep learning models: Fully Convolutional Networks(FCN), U-Net, and SegNet, in both urban and rural scenarios. By partitioning the Urban-Rural dataset of LoveDA for training and testing, it was determined that SegNet excels in detail restoration and boundary handling, while U-Net demonstrates robust adaptability across various scenarios. In contrast, FCN, with its simpler architecture, shows lower segmentation accuracy in certain contexts. This paper offers a comprehensive comparison of the strengths and weaknesses of different models in remote sensing image segmentation and proposes enhancements in model structure and data preprocessing optimization. The findings provide valuable insights for improving the performance of semantic segmentation models and are of significant importance for the precise analysis and practical applications of remote sensing images.

With the maturity of modern science and technology, such as networks and computers, Internet of Things has been widely used in various fields of industry, opening up a new situation for the development of the industry and creating a broader development platform. This paper systematically analyzes the characteristics and changes of the commodity structure, regional structure, market structure, and main structure of export management of agricultural products. The proposed algorithm uses computer technology, network technology, and remote communication technology, electronic, digital, and network—the entire business process of business. The empirical analysis shows that the structure of agricultural product export trade reflects the endowment and comparative advantage of agricultural resources in China. The proposed blockchain technology supports and guides agricultural export enterprises to develop their own brands, strengthen the quality and safety management of agricultural products, and innovate and expand the policy support system for optimizing the structure of agricultural product export trade. By optimizing the export mode of agricultural trade, we can achieve the purpose of increasing the export volume of agricultural products and the total value of trade exports. The experimental results show the effectiveness of the proposed algorithm, which can greatly improve the volume of trade exports and the total value of trade exports.

A refined a priori error analysis of the lowest-order (linear) nonconforming virtual element method (VEM) for approximating a model Poisson problem is developed in both 2D and 3D. A set of new geometric assumptions is proposed on the shape regularity of polytopal meshes. A new error equation for the lowest-order (linear) nonconforming VEM is derived for any choice of stabilization, and a new stabilization using a projection on an extended element patch is introduced for the error analysis on anisotropic elements.

Mechanical forces are fundamental regulators of cell behaviors. However, molecular regulation of mechanotransduction remain poorly understood. Here, we identified the mechanosensitive channels Piezo1 and Piezo2 as key force sensors required for bone development and osteoblast differentiation. Loss of Piezo1, or more severely Piezo1/2, in mesenchymal or osteoblast progenitor cells, led to multiple spontaneous bone fractures in newborn mice due to inhibition of osteoblast differentiation and increased bone resorption. In addition, loss of Piezo1/2 rendered resistant to further bone loss caused by unloading in both bone development and homeostasis. Mechanistically, Piezo1/2 relayed fluid shear stress and extracellular matrix stiffness signals to activate Ca2+ influx to stimulate Calcineurin, which promotes concerted activation of NFATc1, YAP1 and ß-catenin transcription factors by inducing their dephosphorylation as well as NFAT/YAP1/ß-catenin complex formation. Yap1 and ß-catenin activities were reduced in the Piezo1 and Piezo1/2 mutant bones and such defects were partially rescued by enhanced ß-catenin activities.