A Knowledge Discovery System with Support for Model Selection and Visualization

The process of knowledge discovery in databases consists of several steps that are iterative and interactive. In each application, to go through this process the user has to exploit different algorithms and their settings that usually yield multiple models. Model selection, that is, the selection of appropriate models or algorithms to achieve such models, requires meta-knowledge of algorithm/model and model performance metrics. Therefore, model selection is usually a difficult task for the user. We believe that simplifying the process of model selection for the user is crucial to the success of real-life knowledge discovery activities. As opposed to most related work that aims to automate model selection, in our view model selection is a semiautomatic process, requiring an effective collaboration between the user and the discovery system. For such a collaboration, our solution is to give the user the ability to try various alternatives and to compare competing models quantitatively by performance metrics, and qualitatively by effective visualization. This paper presents our research on model selection and visualization in the development of a knowledge discovery system called D2MS. The paper addresses the motivation of model selection in knowledge discovery and related work, gives an overview of D2MS, and describes its solution to model selection and visualization. It then presents the usefulness of D2MS model selection in two case studies of discovering medical knowledge in hospital data—on meningitis and stomach cancer—using three data mining methods of decision trees, conceptual clustering, and rule induction.     

双束强辐照对氧化物弥散强化铁素体型合金强化相稳定性影响

采用双束复合辐照装置,研究了He存在条件下,强辐照对长期时效后的ODS合金中强化相(Y2O3)的稳定性和辐照损伤特征的影响。实验结果表明:双束强辐照下,ODS合金中强化相不稳定,发生聚集长大并造成附近基体中Ti、Y浓度增高,导致空洞尺寸和空洞肿胀增加,并对这一结果从理论上进行解释。     

Parametric Feature Detection

Most visual features are parametric in nature, including, edges, lines, corners, and junctions. We propose an algorithm to automatically construct detectors for arbitrary parametric features. To maximize robustness we use realistic multi-parameter feature models and incorporate optical and sensing effects. Each feature is represented as a densely sampled parametric manifold in a low dimensional subspace of a Hilbert space. During detection, the vector of intensity values in a window about each pixel in the image is projected into the subspace. If the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. The concepts of parameter reduction by normalization, dimension reduction, pattern rejection, and heuristic search are all employed to achieve the required efficiency. Detectors have been constructed for five features, namely, step edge (five parameters), roof edge (five parameters), line (six parameters), corner (five parameters), and circular disc (six parameters). The results of detailed experiments are presented which demonstrate the robustness of feature detection and the accuracy of parameter estimation.     

Human-like natural behavior generation based on involuntary motions for humanoid robots

Human behaviors consist of both voluntary and involuntary motions. Almost all behaviors of task-oriented robots, however, consist solely of voluntary motions. Involuntary motions are important for generating natural motions like those of humans. Thus, we propose a natural behavior generation method for humanoid robots that is a hybrid generation between voluntary and involuntary motions. The key idea of our method is to control robots with a hybrid controller that combines the functions of a communication behavior controller and body balancing controllers. We also develop a wheeled inverted pendulum type of humanoid robot, named “Robovie-III”, in order to generate involuntary motions like oscillation. By applying our method to this robot and conducting preliminary experiments, we verify its validity. Experimental results show that the robot generates both voluntary and involuntary motions.     

Preparation and Property of Acrylic Acid Rare Earth Complex and Its Hydrosilylation

Acrylic acid rare earth complex was prepared. Its chemical composition was determined by chemical and elemental analysis, and its structure as well as properties was characterized using IR, Fluorescence and UV spectrum, and its solubility was also investigated. Meanwhile a kind of elastic functional polymer with rare earth units in the side chains was produced. It is confirmed by IR spectrum that the Si-H bonds really react with acrylic acid rare earth.     

Ultra-high voltage electron microscopy: Past,present, and future

High voltage electron microscopy has shown numerous advantages for the study of natural science, including biology, but it is especially useful in materials science. The most important advantage for materials science is in-situ experiments on detailed processes of the same phenomena that occur in bulk materials. For such in-situ experiments, the specimens should be thicker than a few microns to observe the behavior of lattice effect. The maximum observable thickness of the specimens and other advantages markedly increase with increasing accelerating voltage, and since 1965, two 3 MV instruments have been installed. The present paper is mainly concerned with these 3 MV electron microscopes and their applications to new research fields.     

A Technique to Eliminate Redundant Inter-Processor Communication on Parallelizing Compiler TINPAR

Optimizing inter-processor (PE) communication is crucial for parallelizing compilers for message-passing parallel machines to achieve high performance. In this paper, we propose a technique to eliminate redundant inter-PE messages. This technique utilizes data-flow analysis to find a definition point that corresponds to a use point where the definition and the use occur in different PEs. If several read accesses occurred in the same PE use the data defined at the same definition point in another PE, redundant inter-PE messages are eliminated as follows: only one inter-PE communication is performed for the earliest read access and the previously received data are used for the following read. In order to guarantee the consistency of the data, a valid flag and a sent flag are provided for each chunk of received data. The control of these flags is equivalent to the coherence control by the self invalidation on a compiler aided cache coherence scheme.     

Different Involvement of Vimentin during Invasion by Listeria monocytogenes at the Blood–Brain and the Blood–Cerebrospinal Fluid Barriers In Vitro

The human central nervous system (CNS) is separated from the blood by distinct cellular barriers, including the blood–brain barrier (BBB) and the blood–cerebrospinal fluid (CFS) barrier (BCSFB). Whereas at the center of the BBB are the endothelial cells of the brain capillaries, the BCSFB is formed by the epithelium of the choroid plexus. Invasion of cells of either the BBB or the BCSFB is a potential first step during CNS entry by the Gram-positive bacterium Listeria monocytogenes (Lm). Lm possesses several virulence factors mediating host cell entry, such as the internalin protein family—including internalin (InlA), which binds E-cadherin (Ecad) on the surface of target cells, and internalin B (InlB)—interacting with the host cell receptor tyrosine kinase Met. A further family member is internalin (InlF), which targets the intermediate filament protein vimentin. Whereas InlF has been shown to play a role during brain invasion at the BBB, its function during infection at the BCSFB is not known. We use human brain microvascular endothelial cells (HBMEC) and human choroid plexus epithelial papilloma (HIBCPP) cells to investigate the roles of InlF and vimentin during CNS invasion by Lm. Whereas HBMEC present intracellular and surface vimentin (besides Met), HIBCPP cells do not express vimentin (except Met and Ecad). Treatment with the surface vimentin modulator withaferin A (WitA) inhibited invasion of Lm into HBMEC, but not HIBCPP cells. Invasion of Lm into HBMEC and HIBCPP cells is, however, independent of InlF, since a deletion mutant of Lm lacking InlF did not display reduced invasion rates.     

Human β-Defensin 3 Inhibits Porphyromonas Gingivalis Lipopolysaccharide-Induced Oxidative and Inflammatory Responses of Microglia by Suppression of Cathepsins B and L

Recently, the effects of antibacterial peptides are suggested to have therapeutic potential in Alzheimer’s disease. Furthermore, systemic treatment of Porphyromonas gingivalis (Pg) lipopolysaccharide (LPS) induced Alzheimer’s disease-like neuropathological changes in middle-aged mice. Then, we examined whether human β-defensins (hBDs), antimicrobial peptides produced by the oral mucosa and salivary glands, can suppress Pg LPS-induced oxidative and inflammatory responses by microglia. hBD3 (1 μM) significantly suppressed Pg LPS-induced production of nitric oxide and interleukin-6 (IL-6) by MG6 cells, a mouse microglial cell line. hBD3 (1 μM) also significantly inhibited Pg LPS-induced expression of IL-6 by HMC3 cells, a human microglial cell line. In contrast, neither hBD1, hBD2 nor hBD4 failed to inhibit their productions. Furthermore, hBD3 suppressed Pg LPS-induced p65 nuclear translocation through the IκBα degradation. Pg LPS-induced expression of IL-6 was significantly suppressed by E64d, a cysteine protease inhibitor, and CA-074Me, a known specific inhibitor for cathepsin B, but not by pepstatin A, an aspartic protease inhibitor. Interestingly, hBD3 significantly inhibited enzymatic activities of recombinant human cathepsins B and L, lysosomal cysteine proteases, and their intracellular activities in MG6 cells. Therefore, hBD3 suppressed oxidative and inflammatory responses of microglia through the inhibition of cathepsins B and L, which enzymatic activities are necessary for the NF-κB activation.