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Preparation of Low Ratio Magnesium Ccement by Acid Leaching Treatment of Boron Mud

Journal of Wuhan university of technology(Materials science) 2025年第1期40卷 120-129页

作者： YANG Mei ZHANG Mingzhe CHEN Hao school of Materials science and Engineering Shenyang Jianzhu UniversityShenyang 110168China school of Physical science and technology Shenyang Normal UniversityShenyang 110168China

The effects of liquid-solid ratio and reaction time on the leaching rate of magnesium at room temperature were investigated,as well as the effects of the molar ratio of MgO/MgCl_(2),the amount of water added,and the amount of acid-impregnated slag dosed on the compressive strength and water resistance of *** results showed that the magnesium element in the boron mud could be maximally leached under the conditions of 1:1 concentration of hydrochloric acid at room temperature,liquid-solid ratio of 2.5 mL·g^(-1),and reaction time of 5 h,and the main products were amorphous SiO_(2) as well as a small amount of magnesium olivine which had not been completely *** LR-MOC prepared using the acid-soaked mixture could reach a softening coefficient of 0.85 for 28 d of water immersion when the molar ratio of MgO/MgCl_(2) was 2.2,the amount of water added was 0 g,and the acid-soaked slag dosing was 40 wt%,which also led to an appreciable late-strength,with an increase of 19.4%in compressive strength at 28 d compared to that at 7 *** previous studies,LR-MOC prepared in this way has a final strength phase that is not the more easily hydrolysed 3-phase but the lath-like *** this phenomenon,we analyzed the mechanism and found that,during the acid leaching process,a part of amorphous SiO_(2) dissolved in the acid leaching solution formed a silica sol,in which Mg^(2+)played a bridging role to make the silica sol more *** the addition and hydrolysis of MgO,the silica sol gel coagulation slows down,providing a capping layer to inhibit the hydrolysis of the 5-phase crystals and providing some strength after *** amorphous SiO_(2) in the other part of the acid-impregnated slag generated M-S-H gel with Mg^(2+)and OH-,which synergised with the dense structure composed of interlocking crystals to improve the water resistance of LR-MOC.

关键词： boron mud magnesium chloride-oxygen cement acid immersion water resistance silica sol

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A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen school of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China school of Computer science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

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AI-Enhanced Secure Data Aggregation for Smart Grids with Privacy Preservation

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Computers, Materials & Continua 2025年第1期82卷 799-816页

作者： Congcong Wang Chen Wang Wenying Zheng Wei Gu school of Software Nanjing University of Information Science and TechnologyNanjing210044China school of Information science and Engineering Zhejiang Sci-Tech UniversityHangzhou310018China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China school of Computer science and technology(school of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China school of Computer science(school of Cyber science and Engineering) Nanjing University of Information Science and TechnologyNanjing210044China

As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh Lynn Shacham(BLS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.

关键词： Smart grid data security privacy protection artificial intelligence data aggregation

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Detection and Recognition of Spray Code Numbers on Can Surfaces Based on OCR

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Computers, Materials & Continua 2025年第1期82卷 1109-1128页

作者： Hailong Wang Junchao Shi school of Computer science Zhongyuan University of TechnologyZhengzhou450007China

A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number *** the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection *** terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background *** addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production *** experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line *** Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.

关键词： Can coding recognition differentiable binarization network scene visual text recognition model pruning and quantification transport model

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Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

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Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang Zeng Wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen Wei Yufei Mei Yan Zeng Brain science and Advanced technology Institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan university of science and technology WuhanHubei ProvinceChina school of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

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Local magnetic moment oscillation around an Anderson impurity on graphene

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science china(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 192-201页

作者： Shuai Li Zhen Ma Jin-Hua Gao school of science Hebei University of Science and Technology school of Electronics and Information Zhengzhou University of Light Industry school of Physics and Wuhan National High Magnetic Field Center Huazhong University of Science and Technology

We theoretically investigate the spin resolved Friedel oscillation （FO） and quasiparticle interference （QPI） in graphene induced by an Anderson *** the impurity becomes magnetic,the resulted FO becomes spin dependent,which gives rise to a local magnetic moment oscillation with an envelop decaying as r-2in real space in the doping ***,at half filling,the electron density and local magnetic moment will not oscillate but decay as *** spin resolved FO has both sublattice and spin ***,the local magnetic moment decay at half filling only occurs at one sublattice of graphene,which is quite like the phenomenon observed in the STM experiment (***ález-Herrero et al.,science 352,437 （2016）).We further give an analytic formula about such spin dependent FO based on the stationary phase ***,we study the interference of quasiparticles around the magnetic impurity by calculating the spin dependent Fourier-transformed local density of states （FT-LDOS）.Our work gives a comprehensive understanding about the local magnetic moment oscillation around an Anderson impurity on graphene.

关键词： Friedel oscillation local magnetic moment graphene Anderson impurity

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A Lightweight Multiscale Feature Fusion Network for Solar Cell Defect Detection

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Computers, Materials & Continua 2025年第1期82卷 521-542页

作者： Xiaoyun Chen Lanyao Zhang Xiaoling Chen Yigang Cen Linna Zhang Fugui Zhang school of Mechanical Engineering Guizhou UniversityGuiyang550025China school of Computer science and technology Beijing Jiaotong UniversityBeijing100044China

Solar cell defect detection is crucial for quality inspection in photovoltaic power generation *** the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective ***,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective *** paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these *** network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation ***,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information *** order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target ***,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter ***,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and *** and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon *** results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.

关键词： Defect segmentation multi-scale feature fusion multi-scale attention depthwise separable residual block

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Evolutionary Particle Swarm Optimization Algorithm Based on Collective Prediction for Deployment of Base Stations

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Computers, Materials & Continua 2025年第1期82卷 345-369页

作者： Jiaying Shen Donglin Zhu Yujia Liu Leyi Wang Jialing Hu Zhaolong Ouyang Changjun Zhou Taiyong Li school of Computer science and technology Zhejiang Normal UniversityJinhua321004China school of Future Technologies Jiangxi Institute of Applied Science and TechnologyNanchang330000China school of Computing and Artificial Intelligence Southwestern University of Finance and EconomicsChengdu611130China

The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real *** development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of *** a specific area,achieving higher signal coverage with fewer base stations has become an urgent ***,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as *** a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by *** also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization *** better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base *** experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches *** results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and *** ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.

关键词： Particle swarm optimization effective coverage area global optimization base station deployment

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Efficient OpenMP Based Z-curve Encoding and Decoding Algorithms

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Computers, Materials & Continua 2025年第1期82卷 1313-1327页

作者： Zicheng Zhou Shaowen Sun Teng Liang Mengjuan Li Fengling Xia school of Electronic science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China school of Communications Information Engineering Yunnan Communications Vocational and Technical CollegeKunming650500China Library Yunnan Normal UniversityKunming650500China Faculty of Civil Aviation and Aeronautics Kunming University of Science and TechnologyKunming650500China

Z-curve’s encoding and decoding algorithms are primely important in many Z-curve-based *** bit interleaving algorithm is the current state-of-the-art algorithm for encoding and decoding *** simple,its efficiency is hindered by the step-by-step coordinate shifting and bitwise *** tackle this problem,we first propose the efficient encoding algorithm LTFe and the corresponding decoding algorithm LTFd,which adopt two optimization methods to boost the algorithm’s efficiency:1)we design efficient lookup tables(LT)that convert encoding and decoding operations into table-lookup operations;2)we design a bit detection mechanism that skips partial order of a coordinate or a Z-value with consecutive 0s in the front,avoiding unnecessary iterative *** propose order-parallel and point-parallel OpenMP-based algorithms to exploit the modern multi-core *** results on discrete,skewed,and real datasets indicate that our point-parallel algorithms can be up to 12.6×faster than the existing algorithms.

关键词： Z-curve lookup table OpenMP bit detection mechanism

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Bilevel Optimal Scheduling of Island Integrated Energy System Considering Multifactor Pricing

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Energy Engineering 2025年第1期122卷 349-378页

作者： Xin Zhang Mingming Yao Daiwen He Jihong Zhang Peihong Yang Xiaoming Zhang school of Automation and Electrical Engineering Inner Mongolia University of Science and TechnologyBaotou014010China

In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load *** to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption *** price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption *** benefits and win-win situations are achieved between the upper and lower ***,CPLEX is used to iteratively solve the bilevel optimization *** optimal solution is selected according to the joint optimal discrimination *** results indicate that the sourceload coordinate operation can reduce the upper and lower operation *** the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.

关键词： Bilevel optimal scheduling load aggregator integrated energy operator carbon emission dynamic pricing mechanism

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