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Salmonella Yrb D protein mediates invasion into the host by interacting with β2 integrin

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Journal of Integrative Agriculture 2025年第3期 1181-1197页

作者： Jun cao Jinliang Wang Guanghui Dang Shihao Ding Yao lu Qiu Xu Siguo Liu Shenye Yu State Key Laboratory for Animal Disease Control and Prevention Harbin Veterinary Research Institute Chinese Academy of Agricultural Sciences

Salmonella enterica serovar Typhimurium, the causative agent of gastroenteritis, is one of the most successful intracellular pathogens. Although certain host factors for Salmonella infection have been unveiled, the factors mediating Salmonella entry, particularly the invasion process, remain obscure. Here, we have unearthed β2 integrin,a crucial member of the integrin family, as an important host factor facilitating Salmonella invasion. It is demonstrated that overexpression of β2 integrin promotes Salmonella invasion, while the knockdown of β2 integrin significantly diminishes the extent of invasion. Moreover, Salmonella exhibits specific binding affinity towards β2 integrin, and the block of β2 integrin on cell surface substantially reduces the infection of cells in vitro. The ectodomain soluble protein of β2 integrin neutralized Salmonella infection both in cells(in vitro) and in mice(in vivo). Additionally, Salmonella protein YrbD directly interacts with β2 integrin to facilitate its invasion. To our knowledge, this study showed for the first time that the protein YrbD mediates Salmonella adhesion and internalization into host cells by interacting with β2 integrin. These findings not only broaden our understanding of the mechanisms underlying Salmonella entry, but also identify a prospective target for therapeutic control.

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时间序列分类模型的集成对抗训练防御方法

自动化学报 2025年第1期51卷 144-160页

作者：王璐瑶曹渊刘博涵曾恩刘坤夏元清北京理工大学自动化学院自主智能无人系统全国重点实验室北京100081

深度学习是解决时间序列分类(Time series classification,TSC)问题的主要途径之一.然而,基于深度学习的TSC模型易受到对抗样本攻击,从而导致模型分类准确率大幅度降低.为此,研究了TSC模型的对抗攻击防御问题,设计了集成对抗训练(Advers... 详细信息

深度学习是解决时间序列分类(Time series classification,TSC)问题的主要途径之一.然而,基于深度学习的TSC模型易受到对抗样本攻击,从而导致模型分类准确率大幅度降低.为此,研究了TSC模型的对抗攻击防御问题,设计了集成对抗训练(Adversarial training,AT)防御方法.首先,设计了一种针对TSC模型的集成对抗训练防御框架,通过多种TSC模型和攻击方式生成对抗样本,并用于训练目标模型.其次,在生成对抗样本的过程中,设计了基于Shapelets的局部扰动算法,并结合动量迭代的快速梯度符号法(Momentum iterative fast gradient sign method,MI-FGSM),实现了有效的白盒攻击.同时,使用知识蒸馏(Knowledge distillation,KD)和基于沃瑟斯坦距离的生成对抗网络(Wasserstein generative adversarial network,WGAN)设计了针对替代模型的黑盒对抗攻击方法,实现了攻击者对目标模型未知时的有效攻击.在此基础上,在对抗训练损失函数中添加Kullback-Leibler(KL)散度约束,进一步提升了模型鲁棒性.最后,在多变量时间序列分类数据集UEA上验证了所提方法的有效性.

关键词：时间序列对抗样本对抗训练模型鲁棒性

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基于光谱技术的典型互花米草入侵湿地土壤属性预测研究

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光谱学与光谱分析 2025年第1期45卷 197-203页

作者：陈旭曹思珩杨仁敏陈秋宇李建国徐璐江苏师范大学地理测绘与城乡规划学院地理信息科学系江苏徐州221116

为了高效监测互花米草入侵海岸带湿地生态系统的土壤属性变化,选取江苏省盐城湿地珍禽国家级自然保护区的一处典型互花米草入侵湿地作为研究区,利用随机分层采样方法选取15个样点,在3个深度(0~30、30~60、60~100 cm)共采集45个土壤样品... 详细信息

为了高效监测互花米草入侵海岸带湿地生态系统的土壤属性变化,选取江苏省盐城湿地珍禽国家级自然保护区的一处典型互花米草入侵湿地作为研究区,利用随机分层采样方法选取15个样点,在3个深度(0~30、30~60、60~100 cm)共采集45个土壤样品,测定了土壤可见光-近红外反射光谱和10种土壤理化属性,研究了偏最小二乘和随机森林两种方法的预测能力,分析了不同光谱变换形式对预测精度的影响,探讨了入侵年限和土壤深度作为辅助预测变量的潜力。结果表明:(1)可见光-近红外光谱技术可以较好地预测有机碳、无机碳、全氮、含水量、pH、容重、盐分和黏粒等属性;(2)偏最小二乘回归法比随机森林法更适合监测互花米草入侵湿地的关键土壤理化属性,利用偏最小二乘法对土壤属性建立的预测模型精度(R^(2))在0.341~0.979之间,随机森林方法对土壤属性建立的预测模型精度(R^(2))最高为0.722;(3)基于原始光谱可以获得土壤全氮的最优预测模型(R^(2)为0.769,RMSE为0.091 g·kg^(-1)),而其他土壤属性的最优模型多是基于微分变换或倒数变换建立的模型,微分变换和倒数变换可以有效地提高模型预测精度;(4)模型预测精度在加入入侵年限和土壤深度两个变量后总体上有所提高,其中有机碳、全氮、盐分、pH和容重等属性的预测精度对这两个变量更为敏感,土壤有机碳最优模型的精度(R^(2))从0.794提高到0.806,pH最优模型的精度(R^(2))从0.838提升至0.884,盐分最优模型的精度(R^(2))从0.978提升至0.997。综上所述,可见光-近红外光谱技术在互花米草入侵湿地关键土壤理化属性预测方面具有明显的优越性,通过适当的光谱变换、变量筛选、模型选择等方面可以实现互花米草入侵湿地土壤变化的快速监测。

关键词：互花米草入侵可见光-近红外光谱土壤监测偏最小二乘法随机森林光谱变换

Quantification of polarization distribution from polarizing light microscopy images of ferroelectric single crystals

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Journal of Materials Science & Technology 2023年第30期161卷 1-9页

作者： Jinhui Fan Xiaoyan lu Wenwu cao Functional Materials and Acousto-optic Instruments Institute School of Instrumentation Science and EngineeringHarbin Institute of TechnologyHarbin 150080China School of Civil Engineering Harbin Institute of TechnologyHarbin 150001China Materials Research Institute The Pennsylvania State UniversityUniversity ParkPennsylvania 16802USA

Qualification of polarization can be realized either on a macroscopic scale as an average property by P-E hysteresis measurements or on a nano/micro scale by piezoelectric force microscopy,transmission electron microscopy,scanning electron microscopy,and so ***,visualization and qualification of polarization distribution in the micron to millimeter scale is still a *** light microscopy(PLM)is often used in the study of ferroelectric domain structures mainly for domain patterns.A phe-nomenon called“chromatic polarization”has been observed in transparent ferroelectric crystals by using a crossed-PLM system viewed with white light,which contains rich information about local polariza-tion *** this study,an automatic full-angle light intensity detection(AFALID)algorithm com-bined with colorimetry is developed to analyze the distribution of nonuniform local spontaneous polar-ization distribution in transparent ferroelectric single ***-dependent spontaneous po-larizations from the color analysis for PMN-0.36PT single crystals with single tetragonal domain state are in good coincidence with those extracted from temperature-dependent hysteresis loops and pyroelectric current *** further apply this method to quantify the nonuniform domain distributions with *** non-contact and non-destructive characterization can provide fast and au-tomatic detection of polarization distributions in ferroelectric materials.

关键词： Polarizing light microscopy Polarization distribution Ferroelectric single crystals Chromatic polarization

Distributed Adaptive Output Consensus of Unknown Heterogeneous Non-Minimum Phase Multi-Agent Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 997-1008页

作者： Wenji cao lu Liu Gang Feng Department of Biomedical Engineering City University of Hong KongHong Kong SARChina

This article addresses the leader-following output consensus problem of heterogeneous linear multi-agent systems with unknown agent parameters under directed *** dynamics of followers are allowed to be non-minimum phase with unknown arbitrary individual relative *** is contrary to many existing works on distributed adaptive control schemes where agent dynamics are required to be minimum phase and often of the same relative degree.A distributed adaptive pole placement control scheme is developed,which consists of a distributed observer and an adaptive pole placement control *** is shown that under the proposed distributed adaptive control scheme,all signals in the closed-loop system are bounded and the outputs of all the followers track the output of the leader *** effectiveness of the proposed scheme is demonstrated by one practical example and one numerical example.

关键词： Adaptive pole placement control heterogeneous multi-agent systems leader-following output consensus non-minimum phase

Robust optimization of control command for aerospace vehicles with aerodynamic uncertainty

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Chinese Journal of Aeronautics 2022年第12期35卷 226-241页

作者： Rui cao Yanbin LIU Yuping lu College of Automated Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

To reduce the design burden of Aerospace Vehicles(ASVs)control systems,this paper proposes a multi-constrained robust trajectory optimization method,which provides a good front-end input for the control *** from the conventional aircraft,some control performance of ASVs is not only related to the model parameters,but also affected by the flight ***,the robust optimization method combines this characteristic of ASVs,sets the control performance as one of the optimization objectives,and considers the influence of parameter *** this method,the polynomial chaos expansion algorithm is used to transform the trajectory optimization problem with uncertain parameters into the equivalent deterministic robust trajectory optimization ***,compared with traditional deterministic trajectory optimization methods to illustrate the effectiveness of proposed control optimization method.

关键词： Aerospace vehicle Multi-objective optimization Polynomial chaos Uncertain systems

Day-ahead scheduling based on reinforcement learning with hybrid action space

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Journal of Systems Engineering and Electronics 2022年第3期33卷 693-705页

作者： cao Jingyu DONG lu SUN Changyin School of Automation Southeast UniversityNanjing 210096China School of Cyber Science and Engineering Southeast UniversityNanjing 211189China

Driven by the improvement of the smart grid,the active distribution network(ADN)has attracted much attention due to its characteristic of active *** making full use of electricity price signals for optimal scheduling,the total cost of the ADN can be ***,the optimal dayahead scheduling problem is challenging since the future electricity price is ***,in ADN,some schedulable variables are continuous while some schedulable variables are discrete,which increases the difficulty of determining the optimal scheduling *** this paper,the day-ahead scheduling problem of the ADN is formulated as a Markov decision process(MDP)with continuous-discrete hybrid action ***,an algorithm based on multi-agent hybrid reinforcement learning(HRL)is proposed to obtain the optimal scheduling *** proposed algorithm adopts the structure of centralized training and decentralized execution,and different methods are applied to determine the selection policy of continuous scheduling variables and discrete scheduling *** simulation experiment results demonstrate the effectiveness of the algorithm.

关键词： day-ahead scheduling active distribution network(ADN) reinforcement learning hybrid action space

First-principles insight into the entanglements between superionic diffusion and Li/Al antisite in Al-doped Li1+xAlxGe2–x(PO4)3(LAGP)

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Science China(Technological Sciences) 2020年第9期63卷 1787-1794页

作者： JIANG ChangKun lu Xia cao DaPeng State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing100029China School of Materials Sun Yat-sen UniversityGuangzhou510006China

As an ion conductor, the Al-doped Li1+xAlxGe2-x(PO4)3(LAGP) demonstrates the superionic Li diffusion behavior, however,without the convinced verifications. In this context, the density functional theory(DFT) calculations are employed to clarify the structural origin of the fast Li ion migration kinetics in LAGP solid electrolytes. The calculated results show that doping of Al leads to an emerging high-energy 36 f Li site, which plays an important role in promoting the Li diffusion and can largely lower the Li ion diffusion energy barrier. Moreover, the Li/Al antisite defect is investigated firstly, with which the Li ions are excited to occupy a relatively high energy site in LAGP. The obvious local structural distortion by Li/Al antisite results in the coordination change upon Li diffusion(lattice field distortion), which facilitates the Li diffusion significantly and is probably the main reason to account for the superionic diffusion phenomenon. Therefore, the occupation of Li at high-energy sites should be an effective method to establish the fast Li diffusion, which implies a rewarding avenue to build better Li-ion batteries.

关键词： Li1+xAlxGe2–x(PO4)3(LAGP) Li/Al antisite superionic conductor first-principles calculations Li ion batteries

高光谱预处理方法与多模型在分类判别中的对比研究

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光谱学与光谱分析 2025年第1期45卷 125-132页

作者：居雷于洁吴炎淼李丽卢天丁亚萍束茹欣上海烟草集团有限责任公司技术中心上海200082 上海大学化学系上海200444 上海数之微信息科技有限公司上海200444

高光谱技术能够快速、无损地获取丰富的信息,在植物研究和监测中已成为一种广泛应用的工具。茄科植物作为一种重要的经济农作物,与高光谱技术结合进行研究具有巨大的应用潜力。本研究采用高光谱技术对茄科植物的初烤后不同部位叶片进行... 详细信息

高光谱技术能够快速、无损地获取丰富的信息,在植物研究和监测中已成为一种广泛应用的工具。茄科植物作为一种重要的经济农作物,与高光谱技术结合进行研究具有巨大的应用潜力。本研究采用高光谱技术对茄科植物的初烤后不同部位叶片进行分类研究。采用Field Spec 3光谱辐射仪对293份不同部位的茄科植物粉末样本进行高光谱采样,采用S-G平滑以及一阶导数和二阶导数的方法对数据进行预处理,用于信息增强和去除噪声,并通过偏最小二乘法对数据进行降维,以减少冗余特征。基于降维数据,采样支持向量机、逻辑回归、K近邻、决策树、随机森林和梯度提升决策树这六种机器学习算法建立分类模型。结果显示,在分类任务中,经过一阶导数处理后,支持向量机模型最佳,在训练集和测试集上分别实现了100.0%和84.7%的准确率。经网格参数优化后确定最优参数为:最大深度不限制,最小样本分割数为4,估计器数量为200。参数优化后五折交叉验证准确率为88.1%,训练集准确率为100%,测试集准确率为86.4%。研究结果表明,预处理方法结合降维方法能够增强数据信息使得分类模型能够更好地捕捉茄科植物样本的特征。该研究对于快速、准确、无损地区分茄科植物的部位具有重要意义。

关键词：高光谱部位分类机器学习