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Isobaric enzymatic assays reveal depth-dependent variation in microbial ectoenzyme activities in the deepest ocean on Earth

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science China Earth sciences 2025年第1期68卷 185-194页

作者： Junwei CAO Jiahua WANG Hongge ZHANG Junhao DENG Binbin PAN Jiawang CHEN Li ZHANG Jiasong FANG college of Oceanography and Ecological science Shanghai Ocean University Ocean college Zhejiang University Laboratory for Marine Biology and Biotechnology Qingdao National Laboratory for Marine Science and Technology

Microbial ectoenzymes play essential roles in the transformation and mineralization of organic matter in the ***, conventional methods for measuring microbial ectoenzyme activities(MEAs) in the deep ocean under atmospheric conditions can misrepresent the metabolic activities of indigenous microbial communities. To overcome this limitation, we measured the activities of three microbial ectoenzymes(aminopeptidase, α-glucosidase, and β-glucosidase) under both atmospheric and in situ pressure conditions in seawater collected using pressure-retaining and non-pressure-retaining samplers in the Challenger Deep, Mariana Trench. In the case of aminopeptidase and α-glucosidase, the highest isobaric MEAs were observed in the surface layer(50 m), followed by those at abyssopelagic depths(4,000–6,000 m) for aminopeptidase, hadal realm(10,903 m)for α-glucosidase, while β-glucosidase activity exhibited the highest value at 10,903 m. Furthermore, the isobaric MEAs in hadal waters were commonly found to be higher than the decompressed counterparts, highlighting the importance of pressure-retaining sampling and isobaric enzymatic assays. The half-saturation constant(Km) showed a general decreasing trend with depth,suggesting that the deep ocean microbes might have adapted to the high-pressure and oligotrophic environment by increasing their ectoenzyme's affinity to substrate. Furthermore, particle-free MEAs contribute more to the total MEAs in the deep ocean than particle-associated MEAs, suggesting the significance of cell-associated and dissolved ectoenzymes in ocean *** study provides a foundation for future investigations of MEAs in the ocean and has important implications for understanding the dynamics of microbially mediated biogeochemical cycling in marine ecosystems.

关键词： Pressure-retaining sampling Microbial ectoenzyme activity Deep-sea microbes High pressure Mariana Trench

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Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

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Computers, Materials & Continua 2025年第1期82卷 609-625页

作者： Peng Li Yanrui Wei Lili Yin college of Computer science and Technology Harbin University of Science and TechnologyHarbin150006China

Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price ***,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock *** discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock ***,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation *** results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.

关键词： Stock price prediction generative adversarial network attention mechanism time-series prediction

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Resistance of Cement-based Grouting Materials with Nano- SiO_(2) Emulsion to Chloride Ion Penetration

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Journal of Wuhan University of Technology(Materials science) 2025年第1期40卷 114-119页

作者： LI Shuiping CHENG Jian WEI Chao YUAN Bin YU Chengxiao college of Architectural science and Engineering Yangzhou UniversityYangzhou 225127China

The chloride penetration resistance of cement-based grout materials was improved by nano-silica *** of mixtures containing different nano-silica particles or emulsions were exposed in sodium chloride solutions of specific concentrations with different test *** properties of the mixes were assessed in terms of weight loss and compressive strength.X-ray diffraction(XRD)and scanning electron microscopy(SEM)of mixes were performed to analysis the phase evolution and *** results demonstrated that the introduction of nano-SiO_(2) emulsion significantly decreased the compressive strength loss and calcium hydroxide(CH)crystal content of hydration production,and then enhanced the resistance of cement-based grouting materials to chloride ion *** improvement derives from the filling and pozzolanic effects of nano-SiO_(2) particles,which were incorporated via an emulsion and attributed to a well dispersion in grouting matrix.

关键词： grouting materials nano-SiO_(2)emulsion chloride ion penetration,weight loss strength loss

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An Iterated Greedy Algorithm with Memory and Learning Mechanisms for the Distributed Permutation Flow Shop Scheduling Problem

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Computers, Materials & Continua 2025年第1期82卷 371-388页

作者： Binhui Wang Hongfeng Wang college of Information science and Engineering Northeastern UniversityShenyang110819China

The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent *** iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution ***,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale *** a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the ***,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous *** addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory ***,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom *** last,a discrete adaptive learning rate is employed to enhance the stability of the memory and *** ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large ***,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale *** indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.

关键词： Distributed permutation flow shop scheduling makespan iterated greedy algorithm memory mechanism cooperative reinforcement learning

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Synergistic effect of bonding heterogeneity and phonon localization in introducing excellent thermoelectric properties in layered heteroanionic NdZnSbO material

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Journal of Energy Chemistry 2025年第1期100卷 259-272页

作者： Da Wan Shuwei Tang Shulin Bai Xiaodong Li Peng Ai Wanrong Guo Tuo Zheng college of Materials science and Engineering Liaoning Technical University Faculty of Chemistry Northeast Normal University

Layered rare-earth metal oxides, harnessing the dual properties of oxides and two-dimensional layered materials, exhibit remarkable thermal stability and quantum confinement effects. Therefore, this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound. The coexistence of weak interlayer van der Waals interactions, robust intralayer ionic bonding, and partial covalent bonding leads to remarkable bonding heterogeneity, which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction. The weakened chemical bonds induced by the antibonding states, together with the rattling-like behavior of the Zn atom, culminate in the profound anharmonicity in the layered NdZnSbO compound. The weakening bond and heavy element contribute to the softness of phonon modes, which significantly diminishes the phonon group velocity. The redistribution-dominated four-phonon scattering process spans a large optical gap, which effectively reduces the lattice thermal conductivity. The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06) functional in combination with spin–orbit coupling(SOC) effect. The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy, thus amplifying the power factor. Consequently, an optimal figure-of-merit(ZT) of 3.40 at 900 K is achieved for the n-type NdZnSbO compound. The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.

关键词： Bond strength (chemical)

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A self-adaptive inorganic in-situ separator by particle crosslinking for nonflammable lithium-ion batteries

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Journal of Energy Chemistry 2025年第1期100卷 469-480页

作者： Jiarui Yang Jiuzhou Liu Wenrui Cai Ziyu Zhao Shan Wang Lu He Shanshan Lv Zhiwei Zhu Zhongfeng Ji Guojiang Wen Hua Li Yuanming Zhai Xuewei Fu Wei Yang Yu Wang college of Polymer science and Engineering State Key Laboratory of Polymer Materials Engineering Sichuan University

All-safe liquid-state lithium-ion batteries(ASLS-LIBs) is of great interest as they can potentially combine the safety of all-solid-state batteries with the high performance and low manufacturing cost of traditional liquid-state LIBs. However, the practical success of ASLS-LIBs is bottlenecked by the lack of advanced separator technology that can simultaneously realize high performances in puncturing-tolerability,fire-resistance, and importantly, wetting-capability with non-flammable liquid-electrolytes. Here, we propose a concept of inorganic in-situ separator(IISS) by hybrid-sol physical crosslinking directly onto the electrode surface to address the above challenges. Particularly, the hybrid-sol is designed with silica nanoparticles as the building block and poly(vinylidene difluoride) nanoparticles as the crosslinking agent. The critical factors for controlling the IISS microstructures and properties have been systematically investigated. The advantages of the IISS have been confirmed by its fast wetting with various fireresistant liquid-electrolytes, customizable thickness and porous structures, robust interface with planar or three-dimensional(3D)-structured electrodes, and importantly, unexpected self-adaptability against puncturing. Enabled by the above merits, a fire-resistant ASLS-LIB is successfully assembled and demonstrated with stable electrochemical performance. This sol-crosslinked IISS may open an avenue for the studies on the next-generation separator technology, cell assembling, solid electrolyte processing as well as non-flammable secondary batteries.

关键词： Silica nanoparticles

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Attention Eraser and Quantitative Measures for Automated Bone Age Assessment

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Computers, Materials & Continua 2025年第1期82卷 627-644页

作者： Liuqiang Shu Lei Yu college of Computer and Information science Chongqing Normal UniversityChongqing401331China

Bone age assessment(BAA)aims to determine whether a child’s growth and development are normal concerning their chronological *** predict bone age more accurately based on radiographs,and for the left-hand X-ray images of different races model can have better adaptability,we propose a neural network in parallel with the quantitative features from the left-hand bone measurements for *** this study,a lightweight feature extractor(LFE)is designed to obtain the featuremaps fromradiographs,and amodule called attention erasermodule(AEM)is proposed to capture the fine-grained ***,the dimensional information of the metacarpal parts in the radiographs is measured to enhance the model’s generalization capability across images fromdifferent *** is trained and validated on the RSNA,RHPE,and digital hand atlas datasets,which include images from various racial *** model achieves a mean absolute error(MAE)of 4.42 months on the RSNA dataset and 15.98 months on the RHPE *** to ResNet50,InceptionV3,and several state-of-the-art methods,our proposed method shows statistically significant improvements(p<0.05),with a reduction in MAE by 0.2±0.02 years across different racial ***,t-tests on the features also confirm the statistical significance of our approach(p<0.05).

关键词： Bone age assessment attention eraser quantitative feature metacarpal bones

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Fluorinated poly(p-triphenylene isatin) anion exchange membranes based on hydrophilic hydroxyl side chain modulation for fuel cells

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Journal of Energy Chemistry 2025年第1期100卷 702-709页

作者： Yiman Gu Yanchao Zhang Zhanyu Li Yijia Lei Baozeng Sun Xiaoyu Yu Zhe Wang college of Chemistry and Life science Changchun University of Technology college of Chemical Engineering Changchun University of Technology School of Materials science and Engineering Changchun University of Technology Key Laboratory of Advanced Functional Polymer Membrane Materials of Jilin Province

The development of alkaline fuel cells is moving forward at an accelerated pace,and the application of ether-free bonded polymers to anion exchange membranes （AEMs） has been widely ***,the question of the“trade-off”between AEM ionic conductivity and dimensional stability remains *** strategy of inducing microphase separation to improve the performance of AEM has attracted much attention recently,but the design of optimal molecular structures is still being ***,this work introduced different ratios of 3-bromo-1,1,1-trifluoroacetone （x=40,50,and 60） into the main chain of poly（p-terphenylene isatin）.Because fluorinated groups have excellent hydrophobicity,hydrophilic hydroxyl-containing side chains are introduced to jointly adjust the formation of phase separation *** results show that PTI-PTF50-NOH AEM with the appropriate fluorinated group ratio has the best ionic conductivity and alkali stability under the combined effect of *** has an ionic conductivity of 133.83 mS cm-1at 80°*** addition,the OH-conductivity remains at 89%of the initial value at 80°C and 3 M KOH for 1056 h of *** cell polarization curve based on PTI-PTF50-NOH shows a power density of 734.76 mW cm-2at a current density of 1807.7 mA cm-2.

关键词： Potassium hydroxide

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Effects of the extrusion parameters on microstructure,texture and room temperature mechanical properties of extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 136-146页

作者： Chenjin Zhang Guangyu Yang Lei Xiao Zhiyong Kan Jing Guo Qiang Li Wanqi Jie State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi’an 710072China college of Materials science and Engineering Fuzhou UniversityFuzhou 350108China college of Chemistry and Environmental science Qujing Normal UniversityQujing 655011China

Microstructure,texture,and mechanical properties of the extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy were investigated at different extrusion temperatures(260 and 320℃),extrusion ratios(10:1,15:1,and 30:1),and extrusion speeds(3 and 6 mm/s).The experimental results exhibited that the grain sizes after extrusion were much finer than that of the homogenized alloy,and the second phase showed streamline distribution along the extrusion direction(ED).With extrusion temperature increased from 260 to 320℃,the microstructure,texture,and mechanical properties of alloys changed *** dynamic recrystallization(DRX)degree and grain sizes enhanced as the extrusion ratio increased from 10:1 to 30:1,and the strength gradually decreased but elongation(EL)*** the extrusion speed increased from 3 to 6 mm/s,the grain sizes and DRX degree increased significantly,and the samples presented the typical-rare-earth(RE)*** alloy extruded at 260℃ with extrusion ratio of 10:1 and extrusion speed of 3 mm/s showed the tensile yield strength(TYS)of 213 MPa and EL of 30.6%.After quantitatively analyzing the contribution of strengthening mechanisms,it was found that the grain boundary strengthening and dislocation strengthening played major roles among strengthening *** results provide some guidelines for enlarging the industrial application of extruded Mg-RE alloy.

关键词： Mg-rare earth alloys extrusion temperature extrusion ratio extrusion speed strengthening mechanisms

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An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang Zhang Jiasheng Zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang college of Electronic and Information Engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this ***-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT ***,we evaluate the performance of *** experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBFT grouping reputation XGBoost

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