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China Foundry 2025年第1期22卷 75-82页

作者： lin-fei Xia Wen-bo li Zuo-shan Wei Yu-ying Wu Xiang-fa liu China Key Laboratory for liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationShandong UniversityJinan 250061China Shandong Key Laboratory of Advanced Aluminum Materials and Technology Binzhou Institute of TechnologyBinzhou 256600ShandongChina

Near-eutectic Al-Si alloys are widely used in automotive manufacturing due to their superior wear resistance and high temperature *** of high Si content,the grain refinement of near-eutectic Al-Si alloy has been a problem for many *** this study,the effect of deep cryogenic treatment(DCT)on the microstructure and mechanical properties of Al-12Si-4Cu-2Ni-Mg alloy with addition of Al-Ti-C-B master alloy was fully *** show that the average grain size of the alloy is greatly reduced from 0.92 mm to 0.50 mm,and the eutectic Si and Al7Cu4Ni precipitates are spheroidized and refined in Al-12Si-4Cu-2Ni-Mg after DCT for 24 h and aging *** these changes of microstructures result in a significant increment of about 22.5%in elongation and a slight enhancement of about 6.8%in tensile ***,the refinement of microstructure also significantly improves the fatigue life of the alloy.

关键词： deep cryogenic treatment near-eutectic Al-Si master alloy microstructure mechanical properties

Enhanced Performance of Co-doped Antimony Electrode for pH Measurement in Marine Environments

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Journal of Analysis and Testing 2025年第01期 32-49页

作者： li zong Zhen li Fan Yang Tao Xu Caiyun Zhang Tengfei Xu College of Chemistry and Chemical Engineering Dezhou University Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province College of Pharmaceutical SciencesZhejiang University College of Textile and Clothing Dezhou University Cangnan County Qiushi Innovation Research Institute of Traditional Chinese Medicine

The antimony（Sb） electrode, despite its prevalent use for pH detection in complex environments, suffers from severe potential drift due to poor corrosion resistance, thereby impeding long-term or online applications. Intermetallic compounds show excellent resistance to corrosion and oxidation, presenting a promising avenue for improving the stability of the Sb electrode. Therefore, we fabricate an intermetallic compound-doped Sb electrode by adding various cobalt（Co） contents to improve the stability of the Sb electrode without compromising the inherent pH response. It's observed that the alloy electrode exhibits a significant reduction in surface roughness, corrosion product Sb2O3content, cracks, and Sb exfoliation compared to the pure Sb electrode after the electrochemical tests, and the effect becomes more pronounced as the Co content increases. The electrochemical tests further reveal that the alloy electrode exhibits better corrosion resistance than the pure Sb in various solutions, with the alloy electrode containing 80 at% Sb showing the highest corrosion resistance. Moreover,the alloy electrode containing 80 at% Sb also shows excellent sensitivity and anti-interference ability, high accuracy and reproducibility, low hysteresis, and better long-term stability, especially in seawater. These findings suggest that inexpensive Co doping significantly enhances corrosion resistance, thereby reducing electrode surface alterations and eventually improving the potential stability of pure Sb electrodes without affecting the inherent pH response. Furthermore, the obtained results provide an experimental basis for the long-term operation of the alloy pH electrode in complex environments such as seawater without frequent maintenance.

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A nuclide identification method ofγspectrum and model building based on the transformer

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Nuclear Science and Techniques 2025年第1期36卷 80-93页

作者： Fei li Chu-Yang Luo ying-Zi Wen Sheng Lv Feng Cheng Guo-Qiang Zeng Jian-Feng Jiang Bing-Hai li College of Nuclear Technology and Automation Engineering Chengdu University of TechnologyChengdu 610000China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province Chengdu 610000China Department of Physics Universitat Politècnica de CatalunyaBarcelona 08028Spain Airborne Survey and Remote Sensing Center of Nuclear Industry Shijiazhuang 050000China Hebei Key Laboratory of Airborne Detection and Remote Sensing Technology Shijiazhuang 050000China

In current neural network algorithms for nuclide identification in high-background,poor-resolution detectors,traditional network paradigms including back-propagation networks,convolutional neural networks,recurrent neural networks,etc.,have been limited in research on γ spectrum analysis because of their inherent mathematical *** is difficult to make progress in terms of training data requirements and prediction *** contrast to traditional network paradigms,network models based on the transformer structure have the characteristics of parallel computing,position encoding,and deep stacking,which have enabled good performance in natural language processing tasks in recent ***,in this paper,a transformer-based neural network (TBNN) model is proposed to achieve nuclide identification for the first ***,the Geant4 program was used to generate the basic single-nuclide energy spectrum through Monte Carlo simulations.A multi-nuclide energy spectrum database was established for neural network training using random matrices of γ-ray energy,activity,and *** on the encoder–decoder structure,a network topology based on the transformer was built,transforming the 1024-channel energy spectrum data into a 32×32 energy spectrum sequence as the model *** experiments and adjustments of model parameters,including the learning rate of the TBNN model,number of attention heads,and number of network stacking layers,the overall recognition rate reached 98.7%.Additionally,this database was used for training AI models such as back-propagation networks,convolutional neural networks,residual networks,and long shortterm memory neural networks,with overall recognition rates of 92.8%,95.3%,96.3%,and 96.6%,*** indicates that the TBNN model exhibited better nuclide identification among these AI models,providing an important reference and theoretical basis for the practical application of transformers in the qualitative and quantitativ

关键词： Nuclide identification Neural network Transformer

Real-road NO_(x)and CO_(2)emissions of city and highway China-6 heavy-duty diesel vehicles

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Journal of Environmental Sciences 2025年第3期149卷 330-341页

作者： Zihao Ge Wanyang li Junfang Wang Yachao Wang ying Huang Xin Wang Yunshan Ge School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Weichai Power Co.Ltd. Weifang 261061China Chinese Research Academy of Environmental Sciences Beijing 100012China

The emission of heavy-duty vehicles has raised great concerns *** complex working and loading conditions,which may differ a lot from PEMS tests,raised new challenges to the supervision and control of emissions,especially during real-world ***-board diagnostics(OBD)technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel *** paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data ***-world NO_(x)and CO_(2)emissions of China-6 heavy-duty vehicles have been *** results showed that city heavy-duty vehicles had higher NO_(x)emission levels,which was mostly due to longer time of low SCR temperatures below 180°*** application of novel methods based on 3BMAWalso found that heavy-duty diesel vehicles tended to have high NO_(x)emissions at ***,little difference had been found in work-based CO_(2)emissions,and this may be due to no major difference were found in occupancies of hot running.

关键词： Remote monitor On-Board diagnostics NO_(x)emission CO_(2)emission Heavy-duty vehicles

Attar: RRAM-based in-memory attention accelerator with software-hardware co-optimization

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Science China(Information Sciences) 2025年第03期68卷 371-387页

作者： Bing li ying QI ying WANG Yinhe HAN Information Engineering College Capital Normal University Research Center for Intelligent Computing Systems Institute of Computing TechnologyChinese Academy of Sciences

The attention mechanism has become a pivotal component in artificial intelligence, significantly enhancing the performance of deep learning applications. However, its quadratic computational complexity and intricate computations lead to substantial inefficiencies when processing long sequences. To address these challenges, we introduce Attar, a resistive random access memory(RRAM)-based in-memory accelerator designed to optimize attention mechanisms through software-hardware co-optimization. Attar leverages efficient Top-k pruning and quantization strategies to exploit the sparsity and redundancy of attention matrices, and incorporates an RRAM-based in-memory softmax engine by harnessing the versatility of the RRAM crossbar. Comprehensive evaluations demonstrate that Attar achieves a performance improvement of up to 4.88× and energy saving of 55.38% over previous computing-in-memory(CIM)-based accelerators across various models and datasets while maintaining comparable accuracy. This work underscores the potential of in-memory computing to enhance the efficiency of attention-based models without compromising their effectiveness.

关键词： RRAM computing-in-memory attention pruning quantization

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Disease prediction by network information gain on a single sample basis

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Fundamental Research 2025年第1期5卷 215-227页

作者： Jinling Yan Peiluan li ying li Rong Gao Cheng Bi Luonan Chen School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang 471023China Key Laboratory of Information Fusion Technology of Ministry of Education School of AutomationNorthwestern Polytechnical UniversityXi'an 710072China Longmen Laboratory Luoyang 471003China Key Laboratory of Systems Biology Center for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of SciencesShanghai 200031China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Guangdong Institute of Intelligence Science and Technology Zhuhai 519031China School of life Science and Technology ShanghaiTech UniversityShanghai 201210China

There are critical transition phenomena during the progression of many *** critical transitions are usually accompanied by catastrophic disease deterioration,and their prediction is of significant importance for disease prevention and ***,predicting disease deterioration solely based on a single sample is a difficult *** this study,we presented the network information gain(NIG)method,for predicting the critical transitions or disease state based on network flow entropy from omics data of each *** can not only efficiently predict disease deteriorations but also detect their dynamic network biomarkers on an individual basis and further identify potential therapeutic *** numerical simulation demonstrates the effectiveness of ***,our method was validated by successfully predicting disease deteriorations and identifying their potential therapeutic targets from four real omics datasets,i.e.,an influenza dataset and three cancer datasets.

关键词： Tipping point Network information gain Dynamic network biomarker Disease prediction Network flow entropy Drug target

Steady-state and transient investigation of a small pressurized water reactor ACPR50S for different ATFs based on Bamboo-C code

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Nuclear Science and Techniques 2025年第1期36卷 192-206页

作者： Kun Zhuang ying-Zhen Wang li-Na Deng Yong-Zhan Wang Wen Shang Si-Peng Wang Department of Nuclear Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Small modular reactors have received widespread attention owing to their inherent safety,low investment,and *** pressurized water reactors(SPWRs)have become important candidates for SMRs owing to their high technological *** the Fukushima accident,research on accident-tolerant fuels(ATFs),which are more resistant to serious accidents than conventional fuels,has gradually *** study analyzes the neutronics and thermal hydraulics of an SPWR(ACPR50S)for different ATFs,BeO+UO_(2)−SiC,BeO+UO_(2)−FeCrAl,U_(3)Si_(2)−SiC,and U_(3)Si_(2)−FeCrAl,based on a PWR fuel management code,the Bamboo-C deterministic *** the steady state,the burnup calculations,reactivity coefficients,power and temperature distributions,and control rod reactivity worth were *** transients of the control rod ejection accident for the two control rods with the maximum and minimum reactivity worth were *** results showed that 5%B-10 enrichment in the wet annular burnable absorbers assembly can effectively reduce the initial reactivity and end-of-life reactivity *** BeO+UO2−SiC core exhibited superior neutronic characteristics in terms of burnup and negative temperature reactivity compared with the other three cases owing to the strong moderation ability of BeO+UO_(2)and low neutron absorption of ***,the U_(3)Si_(2)core had a marginally better power-flattening effect than BeO+UO_(2),and the differential worth of each control rod group was similar between different *** the transient of a control rod ejection,the changes in the fuel temperature,coolant temperature,and coolant density were *** maximum difference was less than 10℃ for the fuel temperature and 2℃ for the coolant temperature.

关键词： ACPR50S Small pressurized water reactor ATF Steady Transient

Remediation mechanism of high concentrations of multiple heavy metals in contaminated soil by Sedum alfredii and native microorganisms

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Journal of Environmental Sciences 2025年第1期147卷 179-188页

作者： Zihe Wang Han Zhang ying Xiong lieyu Zhang Jianglong Cui Guowen li Caili Du Kaiyang Wen State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China Beijing Water Science and Technology Institute Beijing 100044China School of Architecture and Civil Engineering Chengdu UniversityChengdu 610106China

Pollution accident of nonferrous metallurgy industry often lead to serious heavy metal pollution of the surrounding *** of contaminated soil is an environmental and sustainable technology,and soil native microorganisms in the process of phytoremediation also participate in the remediation of heavy ***,the effects of high concentrations of multiple heavy metals(HCMHMs)on plants and native soil microorganisms remain ***,further clarification of themechanism of phytoremediation of HCMHMs soil by plants and native soil microorganisms is *** the plant Sedum alfredii(***)to restore HCMHM-contaminated soil,we further explored the mechanism of *** and native soil microorganisms in the remediation of HCMHM *** results showed that(i)*** can promote heavy metals from non-rhizosphere soil to rhizosphere soil,which is conducive to the effect of plants on heavy *** addition,it can also enrich the absorbed heavy metals in its roots and leaves;(ii)native soil bacteria can increase the abundance of signal molecule-synthesizing enzymes,such as trpE,trpG,bjaI,rpfF,ACSL,and yidC,and promote the expression of the pathway that converts serine to cysteine,then synthesize substances to chelate heavy *** addition,we speculated that genes such as K19703,K07891,K09711,K19703,K07891,and K09711 in native bacteria may be involved in the stabilization or absorption of heavy *** results provide scientific basis for *** to remediate heavy metals contaminated soils,and confirm the potential of phytoremediation of HCMHM contaminated soil.

关键词： Microbial remediation Phytoremediation Sedum alfredii

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin li Yanyan Huang Peishu zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

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FX型和FGX型干法分选机在我国的应用

科技情报开发与经济 2005年第14期15卷 121-123页

作者：纵丽英天地科技股份有限公司唐山分公司河北唐山063012

通过介绍FX型和FGX型风选机的结构、工作原理和特点,并从节能、节运、环保的角度,针对动力煤储量丰富的“三北”地区干旱、高寒、缺水的区域特性,指出风力干法选煤技术是一种投资省、见效快、符合国情的行之有效的选煤技术。

关键词： FX型风选机 FGX型风选机干法选煤技术