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利用CKK系统掺用RDF替代燃料的实践

水泥 2025年第2期 26-27页

作者：李利民李贵超阳春海螺水泥有限责任公司广东阳春529600

通过利用现有的CKK系统处置通道掺加RDF替代燃料,将汽化后废气引入分解炉再燃烧利用。实践发现,在窑喂料量稳定前提下,RDF替代燃料使用量得以提升,减少预热器系统有害成分富集,降低熟料生产成本,实现熟料烧成系统的减排、降耗。

关键词： CKK系统 RDF替代燃料减排降耗协同处置

益生菌结合灵芝多糖对高血脂小鼠脂质代谢和抗氧化的影响

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中国食品添加剂 2025年第2期36卷 1-9页

作者：李利敏袁丽雯美乐家(中国)日用品有限公司上海200436 上海中医药大学上海200032

探究益生菌结合灵芝多糖对高血脂小鼠脂质代谢异常和抗氧化酶活性的影响。结果表明:与高脂饲料对照组(HG)相比,活性益生菌组(HG-P)、多糖组(HG-G)、活性益生菌+多糖组(HG-PG)小鼠血清GLU、TC、TG、LDL-C水平均显著降低,HDL-C水平显著升... 详细信息

探究益生菌结合灵芝多糖对高血脂小鼠脂质代谢异常和抗氧化酶活性的影响。结果表明:与高脂饲料对照组(HG)相比,活性益生菌组(HG-P)、多糖组(HG-G)、活性益生菌+多糖组(HG-PG)小鼠血清GLU、TC、TG、LDL-C水平均显著降低,HDL-C水平显著升高,IL-1β、IL-6、TNF-α水平显著降低,小鼠肝脏中TC、TG水平和ALT、AST活性显著降低,SOD、CAT、POD活性显著升高,MDA含量显著降低,其中HG-PG组表现的效果最好。研究还表明益生菌结合灵芝多糖显著提高了小鼠肝脏中AMPKα/Nrf2信号通路AMPKα、Nrf2、HO-1 mRNA的表达水平,同时降低了脂质代谢基因SREBP1、FAS、LP1 mRNA的表达水平。综上所述,益生菌结合灵芝多糖具有改善高血脂小鼠脂质代谢异常、缓解细胞氧化应激损伤、减少肝脏组织脂质积累的作用。

关键词：益生菌灵芝多糖高血脂脂质代谢氧化应激

Determination of Impurity Elements in Pure Cerium Oxide Product

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Journal of Rare Earths 2004年第z1期22卷 335-336页

作者： li Peizhong Chen limin li Jie Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd. Baotou 014010 China Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd.Baotou 014010 China Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd.Baotou 014010 China

Determination of the rare earth impurity in pure cerium oxide is done by *** interference and other factors which affect analytical results were *** accuracy are between 0.81% ～ 11.98% and the recoveries of standard ... 详细信息

关键词： cerium oxide inductively coupled plasma mass spectrometry pure cerium oxide product rare earths

Synthesis and Characterization of a Novel Soluble Diethoxy Phosphoryl Chitosan

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Chinese Journal of Chemistry 2012年第2期30卷 413-417页

作者： Ma,li li,Kerang li,limin liu,Pu Department of Chemistry Zhengzhou UniversityZhengzhouHenan 450001China

A simple and efficient method for the preparation of a novel soluble chitosan derivative, diethoxy phosphoryl chitosan （PH-chitosan）, has been developed. Ph-chitosan was characterized by elemental analysis, FT-IR, NMR, ICP, XRD, TG and SEM, respectively. The chemical identity of PH-chitosan was determined by FT-IR and confirmed by NMR, and those results unequivocally demonstrated that diethoxy phosphoryl groups were grafted onto the amino and hydroxyl groups of chitosan. The results of XRD indicated that the crystalline structure of chitosan was destroyed due to the incorporation of diethoxy phosphoryl group resulting in loss of hydrogen bond. The analysis of TG demonstrated that PH-chitosan was less thermal stable than chitosan. This simple synthetic method provided a new and available approach to prepare a soluble high molecule weight chitosan derivative.

关键词： chitosan diethoxy phosphoryl chitosan synthesis characterization

ON NETWORK-BASED KERNEL METHODS FOR PROTEIN-PROTEIN INTERACTIONS WITH APPliCATIONS IN PROTEIN FUNCTIONS PREDICTION

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Journal of Systems Science & Complexity 2010年第5期23卷 917-930页

作者： limin li Waiki CHING Yatming CHAN Hiroshi MAMITSUKA Department of Mathematics Xi'an Jiaotong University Xi'an 710049 China Advanced Modeling and Applied Computing Laboratory Department of Mathematics The University of Hong Kong Pokfularn Road Hong Kong China Bioinformatics Center Institute for Chemical Research Kyoto University Gokasho Uji Kyoto 611-0011 Japan

Predicting protein functions is an important issue in the post-genomic era. This paper studies several network-based kernels including local linear embedding （LLE） kernel method, diffusion kernel and laplacian kernel to uncover the relationship between proteins functions and protein-protein interactions （PPI）. The author first construct kernels based on PPI networks, then apply support vector machine （SVM） techniques to classify proteins into different functional groups. The 5-fold cross validation is then applied to the selected 359 GO terms to compare the performance of different kernels and guilt-by-association methods including neighbor counting methods and Chi-square methods. Finally, the authors conduct predictions of functions of some unknown genes and verify the preciseness of our prediction in part by the information of other data source.

关键词： Diffusion kernel kernel method Laplacian kernel local linear embedding (LLE) kernel protein function prediction support vector machine.

A review of deep learning methods for pixel-level crack detection

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Journal of Traffic and Transportation Engineering(English Edition) 2022年第6期9卷 945-968页

作者： Hongxia li Weixing Wang Mengfei Wang limin li Vivian Vimlund School of Information Engineering Chang'an UniversityXi'an 710064China School of Computer Baoji University of Arts and SciencesBaoji 721013China School of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China Department of Computer Science and Technology Linkoping UniversityLinköpingSweden

Cracks are a major sign of aging transportation *** detection and repair of cracks is the key to ensuring the overall safety of the transportation *** recent years,due to the remarkable success of deep learning(DL)in the field of crack detection,many researches have been devoted to developing pixel-level crack image segmentation(CIS)models based on DL to improve crack detection accuracy,but as far as we know there is no review of DL-based CIS methods *** address this gap,we present a comprehensive thematic survey of DL-based CIS *** review offers several contributions to the CIS ***,more than 40 papers of journal or top conference most published in the last three years are identified and collected based on the systematic literature review ***,according to the backbone network architecture of the models proposed in them,they are grouped into 10 topics:FCN,U-Net,encoder-decoder model,multi-scale,attention mechanism,transformer,two-stage detection,multi-modal fusion,unsupervised learning and weakly supervised learning,to be ***,our survey focuses on discussing strengths and limitations of the models in each topic so as to reveal the latest research progress in the CIS ***,publicly accessible data sets,evaluation metrics,and loss functions that can be used for pixel-level crack detection are systematically introduced and summarized to facilitate researchers to select suitable components according to their own research ***,we discuss six common problems and existing solutions to them in the field of DL-based CIS,and then suggest eight possible future research directions in this field.

关键词： Crack image segmentation Crack detection Convolutional neural networks Deep learning Systematic literature review

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儿童超说明书用药的伦理问题及对策

中国医学伦理学 2025年第2期38卷 227-231页

作者：李立敏胡海鹏曹晓琴刘小红西安交通大学第一附属医院儿科陕西西安710061

儿童作为一类特殊群体,超说明书用药现象在世界范围内普遍存在。造成儿童超说明书用药的常见原因包括药物研发临床试验阶段缺乏儿童患者数据、药品说明书更新滞后、部分医生执业行为不规范等。儿童超说明书用药是把双刃剑,它可以挽救生... 详细信息

儿童作为一类特殊群体,超说明书用药现象在世界范围内普遍存在。造成儿童超说明书用药的常见原因包括药物研发临床试验阶段缺乏儿童患者数据、药品说明书更新滞后、部分医生执业行为不规范等。儿童超说明书用药是把双刃剑,它可以挽救生命、为探索药品的更多功能提供途径,同时也可能引发药物超适应症滥用的现象,增加发生医疗不良事件的风险。规范儿童超说明书用药,可以保障患儿最佳治疗权益。建议鼓励药企开展儿科新药研发,简化药品说明书修正审批流程,积累儿童超说明书用药循证医学证据,医疗机构规范儿童超说明书用药流程,儿科医师不断提升规范诊疗能力,患儿家属积极配合诊疗,以全方位保障医患双方权益。

关键词：儿童超说明书用药医学伦理医患沟通医疗管理规范诊疗

On Using Physico-Chemical Properties of Amino Acids in String Kernels for Protein Classification via Support Vector Machines

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Journal of Systems Science & Complexity 2015年第2期28卷 504-516页

作者： li limin AOKI-KINOSHITA Kiyoko F CHING Wai-Ki JIANG Hao Institute of Information and System Science Xi'an Jiaotong University Department of Bioinformatics Faculty of EngineeringSoka University Advanced Modeling and Applied Computing Laboratory Department of MathematicsThe University of Hong Kong Department of Mathematics School of InformationRenmin University of China

String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.

关键词： AAindex AA spectrum kernel correlation spectrum kernel physico-chemical properties string kernel weighted spectrum kernel.

Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices

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Computers, Materials & Continua 2024年第7期80卷 527-546页

作者： Amna Khatoon Weixing Wang Asad Ullah limin li Mengfei Wang School of Information Engineering Chang’an UniversityXi’an710064China School of Information Engineering Xi’an Eurasia UniversityXi’an710065China School of Electrical and Electronic Engineering Wenzhou UniversityWenzhou325035China

Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader *** devices efficiently implement a Binary Neural Network(BNN)for road feature extraction,utilizing quantization and compression through a pruning *** modifications resulted in a 28-fold decrease in memory usage and a 25%enhancement in inference speed while only experiencing a 2.5%decrease in *** showcases its superiority over conventional detection algorithms in different road image *** constrained by computer resources and training datasets,our results indicate opportunities for future research,demonstrating that quantization and focused optimization can significantly improve machine learning models’accuracy and operational *** Cortex-M0 gives practical feasibility and substantial benefits while deploying our optimized BNN model on this low-power device:Advanced machine learning in edge *** analysis work delves into the educational significance of TinyML and its essential function in analyzing road networks using remote sensing,suggesting ways to improve smart city frameworks in road network assessment,traffic management,and autonomous vehicle navigation systems by emphasizing the importance of new technologies for maintaining and safeguarding road networks.

关键词： Edge computing remote sensing TinyML optimization BNNs road anomaly detection quantization model compression