辨识智能作动器中迟滞非线性的两种方法

智能化是当今世界的发展趋势。智能材料结构作为研究热点之一,应用于航空、航天、生物及医药等诸多领域。智能作动器与智能传感器是智能材料结构的两个主要研究方向。迟滞现象是存在于大量智能材料中的非线性现象,对整个控制系统可能带来不良影响,如稳定性的恶化甚至丧失等。Preisach模型常用于智能材料中针对迟滞现象的建模。基于一阶滞回曲线获得智能作动器的输入输出数据,从理论上研究了经典Preisach模型两种工程上易实现的辨识方法,并应用到一种真实的智能作动器——WIDS-IA压电型作动器,仿真与实验结果表明,两种辨识方法均有效,且误差在同一数量级。为广泛存在迟滞非线性的智能作动器建模提供了理论依据,并具有工程实用价值。     

网上学生思想政治工作的特点与实践

调研学生的心理状况,结合网络教育从事辅导员工作的实践,指出适应网络时代教育发展做好学生思想政治工作的根本要求.     

任意方位CT切片的获取方法

基于VTK环境提出了一种获取任意方位CT切片的方法：由CT图像序列重构3-D体数据之后，将3-D体数据插值为各向同性，利用VTK实现了3-D体数据内CT切片的绘制显示，并通过平移、旋转变换实现了体数据内其它方向、位置处CT切片的获取．在VTK中的应用实例表明，该方法获取的切片序列有助于医生对同一组织从多个方位进行观察、诊治，在医疗诊断中具有一定的实用价值．     

观赏植物矮化培养研究

通过试验筛选出适合万寿菊、满天星快速繁殖的培养基．矮壮素可使满天星和万寿菊丛苗数量减少，植株生长明显受抑制，使其节间缩短，叶片增厚，叶色浓绿．矮壮素还有使万寿菊根系发达粗壮，分支较少的作用．500mg／L的矮壮素比较适宜矮化培养，既达到了矮化的效果又不至于阻碍植株正常生长，且试管苗株形紧凑、美观．     

Prof. Zhu Zuoyan Met with the INRA Delegation

Prof. Zhu Zuoyan, Vice President of NSFC, met with the National Institute of Agricultural Research (INRA) delegation led by its Deputy Director General, Prof. Guy Riba on Jan. 18, 2007.     

谈公安院校计算机基础教学的改革问题

分析了公安院校当前在计算机基础课程教学中存在的问题，并针对这些问题提出一些改进的措施和建议，以适应当前公安教育的需要。     

Therapeutic applications of bone marrow-derived stem cells in liver transplantation for end-stage liver diseases

Today, liver transplantation (LT) is the only established treatment for end-stage liver diseases. The de- velopment of LT, including OLT, cadaveric LT, split LT, living donor LT (LDLT), brings hopes to patients with these diseases. However, increasing donor shortage, rejection and life-long immunosuppression with its side effects are the major limitations of this therapy strategy. Bone marrow-derived stem cells (BMDSCs) are capable of differentiating into hepatocyte-like cells and contribute to liver injury repair. The microenvironment of liver injury caused by rejection, ischemia/reperfusion, loss of liver mass, recurrence of HCV and "small-for-size syndrome" after LT can attract a variety of bone marrow-derived stem cell population to the peripheral circulation and then migration to the injury liver to promote the hepatic function restoration. Additionally, BMDSCs can also take part in the functional regeneration of living donor liver after LDLT. This participation in liver regeneration may be associated to the interac- tion between SDF-1and its receptor CXCR4, involving HGF, IL-8, MMP9, and VEGF/VEGFR-2. BMDSC with its bio-characteristics could maintain the allograft tolerance from different angles and in different ways. In conclusion, BMDSCs transplantation, as a new assistant therapeutic method for LT, will ex- pand the space of LT, and provide more survival opportunities for the patients suffering liver diseases in the future.     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

信息技术环境下儿童语言发展促进研究

在儿童语言发展特征与人类语言习得理论的基础上,探讨信息技术环境下,利用信息技术促进儿童口语、书面语发展的方法和策略以及要注意的问题。