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INVESTIGATION Of THE EffECT Of TEMPERATURES ONTENSIlE lOAD DROPS Of TITANIUM AllOY

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Acta Metallurgica Sinica(English letters) 1997年第3期10卷 198-202页

作者： Z Zhang ZH Tu l.f. li l.Z. Zhaoand D. Jin (Cryogenic laboratory Chinese Acaderw of Sciences, Beijing 100080, China )H.J lu (Beijing Institute of Aerospace Materials and Technology, Beijing 100076, China) Cryogenic lab Chinese Acad of Sciences Beijing China

low temperature may greatly affect the mechanical properties of materials. Some in-teresting mechanical phenomena were detected at very low temperature. In this study,a multi-sample tensile installation was designed to study the plastic deformation be-havior for Ti-5Al-2.5Sn extra-low-interstitial (Eli) alloy at liquid helium *** special geometrical instability phenomena in low temperature, serrated deforma-tion and multi necking, was studied in detail in this project. Slip and twinning were determined in the process of plastic fiow by SEM/TEM analysis. Efficts of temper-ature and sequential straining on load drops in tensile stress-strain curves were also studied. Optical measurement method was used to gauge the geometrical characteristic of multi-necking specimens. The sensitivity of partial thermoplastic deformation and the equivalency of low tempemture with high velocity of this material were studied by using micro-mechanics *** criterion of geometrical instability has been discussed. A computer simulation of the low temperature instability of plastic fiow in Ti-5Al-2.5Sn Eli alloy has been carried out. A computer model has been established which links the hot dtffusion and the plastic fiow of hcp alloys under assumption that the tempemture is homogeneous within the specimen and that the heat exchange with the thermal bath is the control-ling step in the heat release. The computer simulation of the deformation curves as a function of several mechanincal, geometrical and thermal parameters provides a re-alistic description of the experiments. The experimental data available are discnssed in the light of the computer simulation model.

关键词： mechanical property plastic deformation computer simulation

Pro-resolving lipid mediator reduces amyloid-β42–induced gene expression in human monocyte–derived microglia

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Neural Regeneration Research 2025年第3期20卷 873-886页

作者： Ying Wang Xiang Zhang Henrik Biverstål Nicolas GBazan Shuai Tan Nailin li Makiko Ohshima Marianne Schultzberg Xiaofei li Department of Neurobiology Care Sciences&SocietyDivision of NeurogeriatricsKarolinska InstitutetStockholmSweden Department of Neurology Neuroscience CenterThe First Hospital of Jilin UniversityChangchunJilin ProvinceChina Department of Physiology and Pharmacology Karolinska InstitutetStockholmSweden Department of Biosciences and Nutrition Karolinska InstitutetHuddingeSweden Neuroscience Center of Excellence Louisiana State UniversityNew OrleansLAUSA Department of Medicine SolnaClinical Pharmacology GroupKarolinska University HospitalStockholmSweden

Specialized pro-resolving lipid mediators including maresin 1 mediate resolution but the levels of these are reduced in Alzheimer's disease brain, suggesting that they constitute a novel target for the treatment of Alzheimer's disease to prevent/stop inflammation and combat disease pathology. Therefore, it is important to clarify whether they counteract the expression of genes and proteins induced by amyloid-β. With this objective, we analyzed the relevance of human monocyte–derived microglia for in vitro modeling of neuroinflammation and its resolution in the context of Alzheimer's disease and investigated the pro-resolving bioactivity of maresin 1 on amyloid-β42–induced Alzheimer's disease–like inflammation. Analysis of RNA-sequencing data and secreted proteins in supernatants from the monocyte-derived microglia showed that the monocyte-derived microglia resembled Alzheimer's disease–like neuroinflammation in human brain microglia after incubation with amyloid-β42. Maresin 1 restored homeostasis by down-regulating inflammatory pathway related gene expression induced by amyloid-β42 in monocyte-derived microglia, protection of maresin 1 against the effects of amyloid-β42 is mediated by a re-balancing of inflammatory transcriptional networks in which modulation of gene transcription in the nuclear factor-kappa B pathway plays a major part. We pinpointed molecular targets that are associated with both neuroinflammation in Alzheimer's disease and therapeutic targets by maresin 1. In conclusion, monocyte-derived microglia represent a relevant in vitro microglial model.f.r studies on Alzheimer's disease-like inflammation and drug response for individual patients. Maresin 1 ameliorates amyloid-β42–induced changes in several genes of importance in Alzheimer's disease, highlighting its potential as a therapeutic target for Alzheimer's disease.

关键词： Alzheimer's disease amyloid-β maresin microglia monocyte neuroinflammation resolution RNA-sequencing specialized pro-resolving lipid mediator

Interpretable Machine learning Method for Compressive Strength Prediction and Analysis of Pure fly Ash-based Geopolymer Concrete

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 65-78页

作者： SHI Yuqiong li Jingyi ZHANG Yang li li Key laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas of Ministry of Education Northwest A&F Uni-versityYangling 712100China College of Water Resources and Architectural Engineering Northwest A&F UniversityYangling 712100China Chongqing Key laboratory of Public Big Data Security Technology Chongqing 401420China Chongqing College of Mobile Communication Chongqing 401520China Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina National Rail Transit Electrification and Automation Engineering Technology Research Center(Hong Kong Branch) The Hong Kong Polytechnic UniversityKowloonHung HomHong KongChina

In order to study the characteristics of pure fly ash-based geopolymer concrete(PfGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive *** this study,505 groups of data were collected,and a new database of compressive strength of PfGC was *** order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative *** five machine learning models all showed good compressive strength prediction performance on *** them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,*** R2,MSE,RMSE and MAE of random forest model(Rf)are 0.97,5.17,2.27 and 1.38,*** two models have high prediction accuracy and outstanding generalization *** order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 *** 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide *** temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PfGC than ordinary Portland cement *** importance of curing conditions of PfGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.

关键词： machine learning pure fly ash geopolymer compressive strength feature perception

Merging bound states in the continuum in an open acoustic resonator

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 124-131页

作者： lujun Huang Bin Jia Artem S.Pilipchuk Sibo Huang Chen Shen Almas f.Sadreev Yong li Andrey E.Miroshnichenko School of Physics and Electronic Sciences East China Normal University Institute of Acoustics Tongji University l.V.Kirensky Institute of Physics Department of Mechanical Engineering Rowan University School of Engineering and Technology University of New South Wales at Canberra

Bound states in the continuum （BICs） are perfectly localized resonances despite embedding in the continuum ***,an isolated BIC is very sensitive to the structure ***,we report merging acoustic BICs in a single open resonator,robust against the structure *** find that both symmetry-protected BIC and friedrich-Wintgen BIC are sustained in a single coupled waveguide-resonator *** varying the height and length of the resonator,these two BICs move toward each other and merge into a single one at a critical *** to an individual BIC,the merged BIC is robust against fabrication error because its Q-factor is proportional to Δl-4,whereΔl embodies the structure *** essence of this extraordinary phenomenon is perfectly explained by the two-and three-level approximations of the effective nonHermitian ***,we present direct experimental demonstrations of the moving and merging of BICs in a coupled 3D waveguide-resonator,which are evidenced by the vanishing of the linewidth of fano resonance in the transmission *** results may find exciting applications in designing high-quality acoustic sources,sensors and filters.

关键词： acoustic resonances bound state in the continuum high-Q resonances

Deciphering the role of mtH2O2 in hepatic ischemia-reperfusion injury mechanisms with low-background super-resolution fluorogenic probe

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Science China Chemistry 2025年第1期68卷 297-307页

作者： Bin fang limin Wang Haoqin li Jiaxin Zhang Yang Ding Pan Pan li Bo Peng Hua Bai lin li frontiers Science Center for flexible Electronics Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials &Engineering Northwestern Polytechnical University Institute of flexible Electronics (IfE Future Technologies) Xiamen University

Hepatic ischemia-reperfusion injury（HIRI） is characterized by mitochondrial dysfunction and oxidative stress. Monitoring mitochondrial hydrogen peroxide（mtH2O2） levels in real-time through super-resolution imaging is crucial.f.r elucidating its distribution in live cells and its mechanism of action during HIRI. However, low-background fluorogenic probes have been overlooked in the context of super-resolution imaging. In this study, we developed a low-background fluorogenic probe（MitoWG） with the potential.f.r super-resolution morphology-correlated mitochondrial identification to track the fluctuates of mtH2O2in HIRI. Activation of the desirable fluorescence properties of the probe by mtH2O2was confirmed using structural illumination microscopy（SIM）, enabling high-quality mitochondrial imaging with exceptional specificity and *** in mtH2O2levels were successfully observed in both cellular and rat models of HIRI. furthermore, we associated the decline in mitochondrial redox homeostasis with accelerated mtH2O2production during HIRI, which triggered mitophagy deficiency and led to cell death. In conclusion, Mito-WG possesses excellent photophysical and low-background properties for SIM imaging, making it a promising tool.f.r mtH2O2tracking in HIRI research and clinical diagnosis.

关键词： hepatic ischemia-reperfusion injury low-background mtH2O2-activatable super-resolution imaging fluorogenic probe

A Hybrid Approach for Pavement Crack Detection Using Mask R-CNN and Vision Transformer Model

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Computers, Materials & Continua 2025年第1期82卷 561-577页

作者： Shorouq Alshawabkeh li Wu Daojun Dong Yao Cheng liping li faculty of Engineering China University of GeosciencesWuhan430074China

Detecting pavement cracks is critical.f.r road safety and infrastructure *** methods,relying on manual inspection and basic image processing,are time-consuming and prone to *** deep-learning(Dl)methods automate crack detection,but many still struggle with variable crack patterns and environmental *** study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement *** evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and *** findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and f1-Score across both ***,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and *** high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool.f.r automated pavement crack detection,potentially replacing more traditional methods.

关键词： Pavement crack segmentation transportation deep learning vision transformer Mask R-CNN image segmentation

Joint feature Encoding and Task Alignment Mechanism for Emotion-Cause Pair Extraction

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Computers, Materials & Continua 2025年第1期82卷 1069-1086页

作者： Shi li Didi Sun College of Computer and Control Engineering Northeast Forestry UniversityHarbin150040China

With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant ***-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying *** comprehension is crucial.f.r making informed strategic decisions in various business and societal ***,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause *** address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment *** model consists of two primary components:first,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause ***,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among *** proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and f1 *** results demonstrate that the model achieves an f1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its *** research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-c

关键词： Emotion-cause pair extraction interactive information enhancement joint feature encoding label consistency task alignment mechanisms

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.f.ur 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

Engineering atomic Rb-N configurations to tune radical pathways for highly selective photocatalytic H2O2 synthesis coupled with biomass valorization

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Journal of Energy Chemistry 2025年第1期100卷 215-225页

作者： Jiaye li Shuang Pan Yihuang Chen Qiong liu College of Chemistry and Materials Engineering Wenzhou University Guangdong Provincial Key laboratory of Chemical Measurement and Emergency Test Technology (China) Institute of Analysis Guangdong Academy of Sciences (China National Analytical CenterGuangzhou)

Photocatalytic oxygen reduction for hydrogen peroxide （H2O2） synthesis presents a green and costeffective production ***,achieving highly selective H2O2synthesis remains challenging,necessitating precise control over free radical reaction pathways and minimizing undesirable oxidative ***,we report for the visible light-driven simultaneous co-photocatalytic reduction of O2to H2O2and oxidation of biomass using the atomic rubidium-nitride modified carbon nitride（CNRb）.The optimized CNRb catalyst demonstrates a record photoreduction rate of 8.01 mM h-1for H2O2generation and photooxidation rate of 3.75 mM h-1for furfuryl alcohol to furoic acid,achieving a remarkable solar-to-chemical conversion （SCC） efficiency of up to 2.27%.Experimental characterizations and DfT calculation disclosed that the introducing atomic Rb–N configurations allows for the high-selective generation of superoxide radicals while suppressing hydroxyl.f.ee radical *** is because the Rb–N serves as the new alternative site to perceive a stronger connection position for O2adsorption and reinforce the capability to extract protons,thereby triggering a high selective redox product *** study holds great potential in precisely regulating reactive radical processes at the atomic level,thereby paving the way for efficient synthesis of H2O2coupled with biomass valorization.

关键词： free radical reactions