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Voidage correction method for DEM study of 3D pebble flows in a bed of cycloidal base

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Particuology 2024年第10期93卷 30-40页

作者： Zirui Xia Minglei Shi quan zou Nan Gui Xingtuan Yang Jiyuan Tu Shengyao Jiang Institute of Nuclear and New Energy Technology Collaborative Innovation Center of Advanced Nuclear Energy TechnologyKey Laboratory of Advanced Reactor Engineering and SafetyMinistry of EducationTsinghua UniversityBeijing100084China Department of Engineering Physics Tsinghua UniversityBeijing100084China Department of Automation Tsinghua UniversityBeijing100084China School of Engineering RMIT UniversityMelbourneVIC3083Australia

Voidage(porosity or void fraction)in packed particles(or pebbles)is of fundamental importance in calculating the pressure drop,obtaining the drag,predicting the bed permeability,estimating the neutron streaming,*** the case when particles are deformed,a method of voidage correction during the packing state is proposed using a Discrete Element Method(DEM)simulation of 3D pebble flow inside a bed of cycloidal base.A function to evaluate the remaining volume of a pebble intercepted by horizontal and vertical planes is proposed for voidage *** that,the process of solving voidage distribution is provided in *** this method,the voidage inside the cycloidal-base pebble bed is obtained to refer to reported similar data for *** method can be potentially used for dynamical voidage calculation in CFD-DEM simulation which can get suitable voidage distribution after the correction.

关键词： Voidage Pebbleflow Packed bed Discreteelementmethod Cycloidal base KD-Tree Volume correction

Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning

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Frontiers of Computer Science 2024年第2期18卷 217-229页

作者： Yizheng WANG Xin ZHANG Ying JU Qing LIU quan zou Yazhou ZHANG Yijie DING Ying ZHANG Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China Yangtze Delta Region Institute(Quzhou) University of Electronic Science and Technology of ChinaQuzhou 324000China Beidahuang Industry Group General Hospital Harbin 150088China School of Informatics Xiamen UniversityXiamen 361005China Department of Anesthesiology Hospital(T.C.M)Affiliated to Southwest Medical UniversityLuzhou 646000China Software Engineering College Zhengzhou University of Light IndustryZhengzhou 450002China

Numerous studies have demonstrated that human microRNAs(miRNAs)and diseases are associated and studies on the microRNA-disease association(MDA)have been *** developed a model using a low-rank approximation-based link propagation algorithm with Hilbert–Schmidt independence criterion-based multiple kernel learning(HSIC-MKL)to solve the problem of the large time commitment and cost of traditional biological experiments involving miRNAs and diseases,and improve the model *** constructed three kernels in miRNA and disease space and conducted kernel fusion using *** propagation uses matrix factorization and matrix approximation to effectively reduce computation and time *** results of the experiment show that the approach we proposed has a good effect,and,in some respects,exceeds what existing models can do.

关键词： human miRNA-disease association multiple kernel learning link propagation miRNA similarity disease similarity

SBSM-Pro: support bio-sequence machine for proteins

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Science China(Information Sciences) 2024年第11期67卷 148-163页

作者： Yizheng WANG Yixiao ZHAI Yijie DING quan zou Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China

Proteins play a pivotal role in biological systems. The use of machine learning algorithms for protein classification can assist and even guide biological experiments, offering crucial insights for biotechnological applications. We introduce the support bio-sequence machine for proteins(SBSM-Pro), a model purpose-built for the classification of biological sequences. This model starts with raw sequences and groups amino acids based on their physicochemical properties. It incorporates sequence alignment to measure the similarities between proteins and uses a novel multiple kernel learning(MKL) approach to integrate various types of information, utilizing support vector machines for classification prediction. The results indicate that our model demonstrates commendable performance across ten datasets in terms of the identification of protein function and post translational modification. This research not only exemplifies state-of-the-art work in protein classification but also paves avenues for new directions in this domain, representing a beneficial endeavor in the development of platforms tailored for the classification of biological sequences. SBSM-Pro is available for access at http://***/soft/SBSM-Pro/.

关键词： protein classification machine learning multiple kernel learning sequence alignment

Molecular docking-aided AIEgen design: concept, synthesis and applications

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Science China Chemistry 2024年第8期67卷 2614-2628页

作者： Jian-Qing Zhang Xiao-Yu Xu Fu-Sheng Liu Shu-Qiang Cao Yu-Xin Gui Yi-Wen Su Xiao-Yu He Ji-Yuan Liang You-quan zou Department of Radiation and Medical Oncology Zhongnan Hospital of Wuhan UniversitySchool of Pharmaceutical SciencesWuhan UniversityWuhan 430071China Key Laboratory of Combinatorial Biosynthesis and Drug Discovery Ministry of EducationWuhan UniversityWuhan 430071China Tai Kang Center for Life and Medical Sciences Wuhan UniversityWuhan 430071China Department of Hepatobiliary Pancreatic SurgeryZhongnan Hospital of Wuhan UniversityWuhan 430071China

Aggregate-induced emission luminogens(AIEgens) have been widely used in biological imaging, chemical sensing, and disease treatments. The rational design and construction of AIEgens have received considerable research interests during the last few years. Herein, molecular docking-aided AIEgen design has been reasonably proposed and AIEgen TBQZY with excellent ~1O_(2) generation ability has been synthesized. The newly developed TBQZY could efficiently kill S. epidermidis and methicillinresistant S. epidermidis(MRSE) by tightly binding to bacteria and triggering the accumulation of ~1O_(2) in bacteria. TBQZY specifically regulated the immune system and polarized macrophages from M1 to M2 to accelerate the elimination of biofilm in vivo. In addition, healing acceleration was observed in chronic wounds treated with TBQZY, and side effects were ***, TBQZY had extraordinary potential for combating drug-resistant bacteria in the clinical setting. This research not only provided new concepts for the design of AIEgens, but also shed some lights on the discovery of drugs against drug-resistant bacteria.

关键词： AIEgen molecular docking drug-resistant bacteria biofilm chronic wounds healing

基于机器学习的心脑血管疾病带病体个人自付医疗费用和保险赔付预测

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保险研究 2024年第7期 51-63页

作者：王倩邹全北京工商大学经济学院风险管理与保险学系

心脑血管疾病是老龄人群患病率、死亡率最高的疾病之一,带来了沉重的经济与社会负担。随着我国人口老龄化程度加剧,开发针对带病体的商业健康保险产品显得尤为重要。本文基于详实的历史住院数据,采用机器学习方法对心脑血管疾病人群的... 详细信息

心脑血管疾病是老龄人群患病率、死亡率最高的疾病之一,带来了沉重的经济与社会负担。随着我国人口老龄化程度加剧,开发针对带病体的商业健康保险产品显得尤为重要。本文基于详实的历史住院数据,采用机器学习方法对心脑血管疾病人群的住院费用进行预测,对不同机器学习方法进行预测比较后,采用表现最佳的LightGBM对心脑血管疾病群体进行个人自付费用的测算,分析了性别、年龄、省份、社保类型、婚姻状况、合并症和地区经济条件对个人自付费用的影响,并在此基础上预测了保险理赔情况,发现“年龄”是影响理赔的主要因素。本研究结果可为保险公司设计创新型商业健康保险产品提供借鉴。

关键词：心脑血管疾病机器学习住院费用预测赔付预测商业健康保险

Correlations of transcranial sonography of substantia nigra characteristics with MRI iron deposition on substantia nigra in patients with Parkinson disease

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中国医学影像技术 2024年第8期40卷 1160-1163页

作者： zou quan CHEN Fei MENG Wenyu ZHENG Hong Department of Ultrasound Medicine the First Hospital of Lanzhou UniversityLanzhou 730000China

Objective To explore the correlations of transcranial sonography of substantia nigra(SN-TCS)characteristics with MRI iron deposition on substantia nigra in patients with Parkinson disease(PD).Methods Data of SN-TCS and craniocerebral MRI in 120 PD patients were retrospectively *** patients were divided into iron deposition positive group(positive group,n=46)and iron deposition negative group(negative group,n=74)according to quantitative susceptibility mapping(QSM)*** parameters of SN-TCS and MRI were compared between groups(both P0.05).Strong echo area of substantia nigra and S/M based on SN-TCS were both low-medium positively correlated with substantia nigra QSM value showed on MRI(r=0.497,0.529,both P<0.001).Conclusion SN-TCS characteristics of PD patients were correlated with MRI iron deposition on substantia nigra,among which strong echo area and S/M were valuable for evaluating iron deposition on substantia nigra.

关键词： Parkinson disease substantia nigra iron ultrasonography magnetic resonance imaging

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市政路灯照明电气系统无功补偿研究

中国照明电器 2024年第7期 30-31,91页

作者：邹泉深圳市全局照明科技有限公司广东深圳518000

城市照明系统是现代都市不可或缺的基础设施之一,它不仅关系着市民的夜间出行安全,也是城市美观和文明的象征。然而,传统市政路灯系统存在能耗高、效率低的问题,与当前节能减排和可持续发展目标相悖。因此,发展节能型路灯系统成为市政... 详细信息

城市照明系统是现代都市不可或缺的基础设施之一,它不仅关系着市民的夜间出行安全,也是城市美观和文明的象征。然而,传统市政路灯系统存在能耗高、效率低的问题,与当前节能减排和可持续发展目标相悖。因此,发展节能型路灯系统成为市政照明领域的重要方向。在此背景下,无功补偿的应用显得尤为重要。该项技术能够有效降低路灯系统能耗,提升电力系统运行效率,减少能量损失。同时无功补偿中的TSC技术,进一步提高了市政路灯的节能效果,满足了社会对资源节约的要求。

关键词：市政路灯照明电气系统无功补偿

A Machine Learning Method for Differentiating and Predicting Human-Infective Coronavirus Based on Physicochemical Features and Composition of the Spike Protein

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Chinese Journal of Electronics 2021年第5期30卷 815-823页

作者： WANG Chao zou quan Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Hainan Key Laboratory for Computational Science and Application Hainan Normal University

Several Coronaviruses(CoVs) are epidemic pathogens that cause severe respiratory syndrome and are associated with significant morbidity and mortality. In this paper, a machine learning method was developed for predicting the risk of human infection posed by CoVs as an early warning system. The proposed Spike-SVM(Support vector machine) model achieved an accuracy of 97.36% for Human-infective CoV(HCoV) and Nonhuman-infective CoV(Non-HCoV) classification. The top informative features that discriminate HCoVs and Non-HCoVs were identified. Spike-SVM is anticipated to be a useful bioinformatics tool for predicting the infection risk posed by CoVs to humans.

关键词： Biomolecular structure, configuration, conformation, and active sites Biomolecular interactions, charge transfer complexes Biology and medical computing Coronavirus Virus-host association Spike protein Machine learning

步态参数与黑质强回声在帕金森病早期诊断与病情进展的关联性研究

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中国超声医学杂志 2024年第3期40卷 245-248页

作者：邹全陈飞孟文玉郑红石博兰州大学第一医院超声医学科

目的研究旨在探讨帕金森病(PD)经颅超声检查中黑质强回声与PD临床特征之间的相关性，以进一步了解黑质强回声在PD诊断和病情评估中的意义，为PD早期诊治提供新的思路。方法研究纳入确诊的50例原发性PD患者作为实验组，并选定性别及年... 详细信息

目的研究旨在探讨帕金森病(PD)经颅超声检查中黑质强回声与PD临床特征之间的相关性，以进一步了解黑质强回声在PD诊断和病情评估中的意义，为PD早期诊治提供新的思路。方法研究纳入确诊的50例原发性PD患者作为实验组，并选定性别及年龄比例与实验组相匹配的50例健康成年人作为对照组。对其临床特征进行详细记录，包括年龄、性别、病程、症状表现等。同时，采用经颅超声技术对所有患者进行黑质强回声检测。采用相关性分析、卡方检验和线性回归分析等方法，分析黑质强回声与PD临床特征之间的关联性。结果在黑质强回声检测方面，发现79例患者存在黑质强回声现象。在临床特征方面，存在黑质强回声的患者其病程更长、症状表现更严重(P<0.05)。相关性分析显示，黑质强回声与PD病程之间存在显著正相关性(r=0.672,P<0.01)。结论黑质强回声与PD临床特征之间存在显著关联性。因此，黑质强回声检测可以作为评估PD病情严重程度和病程进展的重要指标。建议在未来的临床实践中进一步推广应用黑质强回声检测技术，以提高PD诊断和治疗的灵敏度。

关键词：帕金森病步态参数黑质强回声 TCS 相关性