Evaluation of electrochemical properties of antibacterial ZnO layers deposited to 316LVM steel using atomic layer deposition

The presence of a biofilm can lead to the disappearance of the surrounding bone tissue and, as a result, disturb the osseointegration process. Unfortunately, both in the case of instability of the implant and long-term bacterial infections, there is often a need for reoperation as well as replacement of the implant, which in turn is associated with huge costs, but most of all discomfort for the patient associated with long-term hospitalization. In order to limit this unfavorable process, the physicochemical properties of the surface layer of implants are indicated. Therefore, the paper proposes applying a layer with antibacterial effect on the surface of 316LVM steel used in bone surgery. As part of the work, the ZnO layer was applied using the atomic layer deposition method with different parameters of the application process (different number of cycles at constant temperature). In the first stage, pitting corrosion resistance tests were carried out using the potentiodynamic method and studies using electrochemical impedance spectroscopy. The surface morphology tests using a scanning electron microscope were also complemented. Obtained results may form the basis for the development of more detailed criteria for the assessment of the final quality of medical devices used in the skeletal system.     

一种基于改进高斯过程隐变量模型的多角度人脸识别算法

针对传统谱算法在人脸识别中的局限,该文提出一种基于改进高斯过程隐变量模型(GP-LVM)的多角度人脸识别算法。首先,通过高斯过程(GP)对人脸流形建立概率模型,得到高斯过程隐变量模型(GP-LVM);其次,分析GP-LVM得到共有信息(shared information)和独有信息(private information),利用概率最大化与拉格朗日乘子法得到参照矩阵和参照值;最后,实现多角度人脸识别。选取Yale,JAFFE,FERET,CMU-PIE 4类数据集进行对比实验,实验结果表明:该文提出的算法可以有效地识别多角度人脸,针对无角度人脸识别也具有良好的效果。     

The effect of surface roughness on the efficiency of the cyclic potentiodynamic passivation (CPP) method in the improvement of general and pitting corrosion resistance of 316LVM stainless steel

The influence of surface roughness on the efficiency of a cyclic potentiodynamic passivation (CPP) method employed to increase the general and pitting corrosion resistance of 316LVM stainless steel was investigated. The results show that a decrease in surface roughness of both the surface on which the passive film was formed naturally and by the CPP method, results in an increase in general corrosion resistance of the material, while for the CPP-modified surface, a notable increase in pitting corrosion resistance was also observed. It was further demonstrated that the CPP method is highly effective in increasing the general and pitting corrosion resistance of 316LVM, and that its efficiency does not depend on the surface roughness.     

基于LVM 的系统扩容技术研究

近年来,随着大数据业务的使用,系统在运行时会产生大量的数据信息与日志文件并保存在磁盘中。由于在系统规划初期,对系统分区大小规划预期不足,很难合理规划磁盘空间,造成后期系统运行中经常出现系统分区磁盘不足的问题。当发生此类告警时,通常的分区很难动态调整大小,通常采用暂停业务,更换磁盘,数据备份与恢复的方式,该方式操作困难,程序复杂,有数据丢失的风险。在Linux系统里使用LVM(逻辑卷)技术,支持在线空间扩容,可以在用户无感知的情况下扩展系统分区容量,达到合理利用磁盘空间的目的。本文介绍了LVM技术,并在Linux系统里将分区做成逻辑卷,达到合理利用磁盘空间的目的。     

Linux上LVM快照数据一致性迁移

在基于Linux的生产系统中,人们越来越普遍地利用LVM的快照技术做数据一致性迁移和文档版本回溯,但是对于性能分析方面目前还没有相关论述文章。详细介绍LVM快照数据一致性迁移,着重分析迁移失真度以及由此带来的生产系统性能损耗,并通过实验证明性能损耗不会超过10%的结论。     

用于网络存储系统的存储空间动态分配方法

提出一种在网络存储系统中动态分配存储空间的方法,可以在保持用户视图的逻辑空间大小不变的情况下,按需分配用户实际所用存储空间。与传统基于逻辑卷管理器的动态分配方法相比,该方法无须修改文件系统元数据,具有更好的可扩展性,已应用于TransCom系统中。实践表明,它实现简单、开销较小,可满足实际使用需求。     

在PC Cluster机群中实现批量常规地震资料数据处理

LinuxPC服务器的磁带I/O能力较差,数据传输也受到网络带宽的限制,在大规模地震数据处理中存在严重的瓶颈。本文通过对PC机群的体系结构的分析,结合OMEGA应用软件用于常规处理的实际需求,从配置外置盘阵、磁带机,连接自动带库,合并多块磁盘成一个大卷,增加网络接口以提高传输带宽等多方面介绍了PC机群整体性能的技术改进过程,以满足常规地震数据处理的需要。     

基于逻辑卷管理的虚拟网络存储的设计

随着数据爆炸性的增长，虚拟网络存储已经成为目前的主流技术，它能方便地实现数据共享和统一管理。在分析了虚拟网络存储相关技术的基础上，采用逻辑卷管理（logical volume manager，LVM）和网络块设备（network block device，NBD）技术，提出了在TCP／IP网络环境下，在设备驱动层实现虚拟网络存储的新方法：通过LVM和NBD将网络上的存储设备虚拟成本地磁盘，使得用户可以透明地使用存储资源，从而实现海量存储。并给出了基于LVM虚拟网络存储的快照技术应用实例，证明了LVM虚拟网络存储的可用性。     

GaAs中碳的补偿率对红外吸收方法测定其浓度的影响

通过直接测量GaAs中碳(C)的局域振动模(LVM)红外吸收带随其荷电态的变化,研究了GaAs中碳的LVM红外吸收与其荷电态的关系。结果表明,该吸收带对C的荷电态是不敏感的,红外吸收测定GaAs中碳浓度的方法对不同C补偿率的样品都是适用的。     

Latent variable model predictive control for trajectory tracking in batch processes: Alternative modeling approaches

Several Latent Variable Model (LVM) structures for modeling the time histories of batch processes are investigated from the view point of their suitability for use in Latent Variable Model Predictive Control (LV-MPC) [1] for trajectory tracking and disturbance rejection in batch processes. The LVMs are based on Principal Component Analysis (PCA). Two previously proposed approaches (Batch-Wise Unfolding (BWU) and Observation-Wise with Time-lag Unfolding (OWTU)) for modeling of batch processes [2] are incorporated in the LV-MPC and the benefits and drawbacks of each are explored. Furthermore, a new modeling approach (Regularized Batch-Wise Unfolding (RBWU)) is proposed to overcome the shortcomings of each of the previous modeling approaches while keeping the major benefits of both. The performances of the three latent variable modeling approaches in the course of LV-MPC for trajectory tracking and disturbance rejection are illustrated using two simulated batch reactor case studies. It is seen that the RBWU approach models the nonlinearity and time-varying properties of the batch almost as accurately as BWU approach, but needs fewer observations (batches) for model identification and results in a smoother PCA model. Recommendations are then given on which modeling approach to use under different scenarios.