基于最小二乘支持向量机的故障诊断方法*

提出了一种小波包分析与最小二乘支持向量机相结合的机械设备故障诊断模型.首先对故障信号功率谱进行小波分解,简化了故障特征向量的提取,然后采用最小二乘支持向量机进行故障诊断.在该模型中,用二次损失函数取代支持向量机中的不敏感损失函数,将不等式约束条件变为等式约束,从而将二次规划问题转换为线性方程组的求解,并提出对核函数的σ参数进行动态选取.仿真结果表明:该模型可以取得较高的故障诊断准确率.     

快速的层次树集合分划编码算法*

设计了一个改进算法,它仅需对小波分解矩阵进行一遍扫描即可确定层次树集合分划编码(SPIHT)算法所需的所有D(i,j)和L(i,j)重要性并完成对所有(i,j)子系数的编码,使得按照SPIHT的排序方法编码时只需查找存放D(i,j)和L(i,j)的重要性及(i,j)子系数的编码表,从而大大提高了SPIHT的编码速度.     

基于邻域彩色变化矢量场的图像边缘检测技术研究*

首先进行了边缘检测系统结构设计,建立了图像邻域彩色变化矢量场的数理模型,提出了用图像邻域彩色变化方向锐度描述图像边缘,进而应用模糊聚类自适应检测边缘.实验表明:与基于梯度的边缘检测技术相比,该方法在噪声抑制以及边缘准确定位上均取得了好的效果,是一种应用广泛的优秀边缘检测算法.     

具有中介状态和失效相关时 表决工程系统的可靠性分析

传统的模糊可靠性理论由于引入了模糊工作状态,因素处理方法不断细化,使得分析模型越来越复杂,计算方法过于烦琐,难以为工程实际所应用,特别是对于表决工程系统。采用具有“安全-中介-失效”三级工作模式的单元和系统的可靠性分析方法,运用随机事件的S并运算和T交运算规则,给出了具有中介状态的表决工程系统可靠性向量的计算方法和步骤,可靠性分析的结果是求出系统的安全概率（可靠度）PR、中介概率PM和失效概率PF,并构成可靠性向量［PR,PM,PF］。同时考虑了系统各单元间失效相关性问题,合理地给出单元间的失效相关性参数λ∈［0,1］之值,并利用Sλ和Τλ算子计算考虑各结构失效相关性时表决工程系统的可靠性向量。     

含有不可控变迁的Parikh约束的Petri网控制器综合

针对基于Petri网建模的离散事件系统关于Parikh向量的不等式约束反馈控制器设计问题,对Parikh向量的不等式约束条件中存在不可控变迁的情况进行分析.将约束条件分为可控部分与不可控部分,即允许约束和禁止约束,并通过矩阵变换方法对含有不可控变迁的禁止约束部分进行处理,将禁止约束转化为允许约束,从而设计出相应的控制器.实例表明,该方法结构清晰,计算简单,用于混合约束条件中,能大大减少计算量,在复杂Petri网模型中效果更为明显.     

基于三矢量模型预测电流控制的共模电压抑制策略

针对永磁同步电机(PMSM)驱动系统中存在的共模电压高、电流脉动大的问题,提出将无零矢量调制(NSPWM)方法与三矢量模型预测电流控制算法结合进行控制。已有的单矢量模型共模电压抑制策略电压矢量方向固定,可选矢量范围有限,电流脉动仍较大。而三矢量模型预测电流控制共模电压抑制策略基于NSPWM在每个扇区利用3个非零矢量合成目标电压矢量,矢量范围覆盖广。结合无差拍电流控制,在实现共模电压抑制的同时,还能减小电流脉动,提高系统动态响应。通过仿真和试验验证了所提控制策略的有效性。     

基于平流矢量场和弥散流改进的几何活动轮廓模型

几何活动轮廓通过水平集演化捕获目标边界,然而传统方法忽略了前景物体涉及的全局运动及局部形变,从本质上限制了轮廓的动态谐调范围。提出一种由隐式流驱动的几何活动轮廓方法,用于分割形变对象的动态轮廓。根据流体力学,对平流及弥散的隐式流进行建模,从而直接引导水平集的更新。根据图像序列之间有限的运动观测,采用具有平滑和稀疏项的回归算法以拟合平流矢量场。然后,引入受空间梯度约束的非均匀弥散方程,将最终叠加的隐式流用于水平集演化。提出的几何活动轮廓方法构成了一个统一的扩展框架,保留了已有模型对轮廓拓扑变化的适应性。对多个场景下的动态轮廓分割实验表明,提出方法能准确地分割具有全局运动及不规则形变的前景目标,且具有收敛速度快、稳定性强的优点。     

Development of Covalent Chitosan-Polyethylenimine Derivatives as Gene Delivery Vehicle: Synthesis,Characterization, and Evaluation

There is an increasing interest in cationic polymers as important constituents of non-viral gene delivery vectors. In the present study, we developed a versatile synthetic route for the production of covalent polymeric conjugates consisting of water-soluble depolymerized chitosan (dCS; M_W 6–9 kDa) and low molecular weight polyethylenimine (PEI; 2.5 kDa linear, 1.8 kDa branched). dCS-PEI derivatives were evaluated based on their physicochemical properties, including purity, covalent bonding, solubility in aqueous media, ability for DNA condensation, and colloidal stability of the resulting polyplexes. They were complexed with non-integrating DNA vectors coding for reporter genes by simple admixing and assessed in vitro using liver-derived HuH-7 cells for their transfection efficiency and cytotoxicity. Using a rational screening cascade, a lead compound was selected (dCS-Suc-LPEI-14) displaying the best balance of biocompatibility, cytotoxicity, and transfection efficiency. Scale-up and in vivo evaluation in wild-type mice allowed for a direct comparison with a commercially available non-viral delivery vector (in vivo-jetPEI). Hepatic expression of the reporter gene luciferase resulted in liver-specific bioluminescence, upon intrabiliary infusion of the chitosan-based polyplexes, which exceeded the signal of the in vivo jetPEI reference formulation by a factor of 10. We conclude that the novel chitosan-derivative dCS-Suc-LPEI-14 shows promise and potential as an efficient polymeric conjugate for non-viral in vivo gene therapy.     

Adenovirus-Mediated Inducible Expression of a PD-L1 Blocking Antibody in Combination with Macrophage Depletion Improves Survival in a Mouse Model of Peritoneal Carcinomatosis

Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in a growing number of malignancies. However, overcoming primary or secondary resistances is difficult due to pharmacokinetics issues and side effects associated with high systemic exposure. Local or regional expression of monoclonal antibodies (mAbs) using gene therapy vectors can alleviate this problem. In this work, we describe a high-capacity adenoviral vector (HCA-EFZP-aPDL1) equipped with a mifepristone-inducible system for the controlled expression of an anti-programmed death ligand 1 (PD-L1) blocking antibody. The vector was tested in an immune-competent mouse model of colorectal cancer based on implantation of MC38 cells. A single local administration of HCA-EFZP-aPDL1 in subcutaneous lesions led to a significant reduction in tumor growth with minimal release of the antibody in the circulation. When the vector was tested in a more stringent setting (rapidly progressing peritoneal carcinomatosis), the antitumor effect was marginal even in combination with other immune-stimulatory agents such as polyinosinic-polycytidylic acid (pI:C), blocking mAbs for T cell immunoglobulin, mucin-domain containing-3 (TIM-3) or agonistic mAbs for 4-1BB (CD137). In contrast, macrophage depletion by clodronate liposomes enhanced the efficacy of HCA-EFZP-aPDL1. These results highlight the importance of addressing macrophage-associated immunoregulatory mechanisms to overcome resistance to ICIs in the context of colorectal cancer.     

基于三维特征向量的非侵入式电热负荷细分算法

非侵入式负荷监测分解（NILMD）技术是当前居民用能服务深化提升和电力供需互动的重要数据获取手段,然而当前工程上应用广泛的事件驱动型NILMD技术一直无法准确细化分解电热负荷。针对这一问题,文中提出了一种基于三维特征向量的典型电热负荷细化分解算法。首先,基于有功、无功功率和电流谐波等电气负荷特征采用事件检测方法提取电热事件,在有功功率的基础上,引入运行时长、频繁启停次数等非电气负荷特征共同构建三维特征向量电器模型。然后,采用序贯覆盖法设计典型电热负荷细化分解命题学习规则和细化分解算法。最后,基于实证实验数据进行分解验证,发现4种典型电热负荷的细化分解准确率超过85%。实验结果表明,文中所提典型电热负荷细化分解算法有效地提高了4种典型电热负荷分解的准确率。