Variants of the 3' region of the cagA gene in Helicobacter pylori isolates from patients with different H. pylori-associated diseases

The CagA protein of Helicobacter pylori is an immunogenic antigen of variable size and unknown function that has been associated with increased virulence as well as two mutually exclusive diseases, duodenal ulcer and gastric carcinoma. The 3' region of the cagA gene contains repeated sequences. To determine whether there are structural changes in the 3' region of cagA that predict outcome of H. pylori infection, we examined 155 cagA gene-positive H. pylori isolates from Japanese patients including 50 patients with simple gastritis, 40 with gastric ulcer, 35 with duodenal ulcer, and 30 with gastric cancer. The 3' region of the cagA gene was amplified by PCR followed by sequencing. CagA proteins were detected by immunoblotting using a polyclonal antibody against recombinant CagA. One hundred forty-five strains yielded PCR products of 642 to 651 bp; 10 strains had products of 756 to 813 bp. The sequence of the 3' region of the cagA gene in Japan differs markedly from the primary sequence of cagA genes from Western isolates. Sequence analysis of the PCR products showed four types of primary gene structure (designated types A, B, C, and D) depending on the type and number of repeats. Six of the seven type C strains were found in patients with gastric cancer (P < 0.01 in comparison to noncancer patients). Comparison of type A and type C strains from patients with gastric cancer showed that type C was associated with higher levels of CagA antibody and more severe degrees of atrophy. Differences in cagA genotype may be useful for molecular epidemiology and may provide a marker for differences in virulence among cagA-positive H. pylori strains.     

Kinematic properties of human arm reaching movements in a three-dimensional space

In this study, kinematic properties of human arm reaching movements have been analyzed by use of experimental results of arm trajectories observed in a three-dimensional (3D) space. In the beginning, hand paths obtained by the experiments are kinematically analyzed to pursue their linearity, and we successfully specify a plane on which a hand moves. In the next place, the hand speed profile is calculated by use of position data observed by the experiment in a 3D space. Besides, the hand speed profile is also analytically produced under the minimum jerk criterion with respect to the displacement along the hand path. These observed and produced trajectories are compared, and the similarity of two trajectories has been demonstrated. As a result of the analyses for path and the speed profile of a hand, kinematic properties of human arm trajectories have been identified.     

Group impressions as dynamic configurations: The tensor product model of group impression formation and change.

Group impressions are dynamic configurations. The tensor product model (TPM), a connectionist model of memory and learning, is used to describe the process of group impression formation and change, emphasizing the structured and contextualized nature of group impressions and the dynamic evolution of group impressions over time. TPM is first shown to be consistent with algebraic models of social judgment (the weighted averaging model; N. Anderson, 1981) and exemplar-based social category learning (the context model; E. R. Smith & M. A. Zárate, 1992), providing a theoretical reduction of the algebraic models to the present connectionist framework. TPM is then shown to describe a common process that underlies both formation and change of group impressions despite the often-made assumption that they constitute different psychological processes. In particular, various time-dependent properties of both group impression formation (e.g., time variability, response dependency, and order effects in impression judgments) and change (e.g., stereotype change and group accentuation) are explained, demonstrating a hidden unity beneath the diverse array of empirical findings. Implications of the model for conceptualizing stereotype formation and change are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Overview of JSME flaw evaluation code for nuclear power plants

A Japanese flaw evaluation code for nuclear power plant components has been developed at the Japan Society of Mechanical Engineers (JSME). The code prescribes methods for the evaluation of flaws, which are detected during inservice inspection for pressure vessels and pipes in nuclear power plants. This paper describes the basic flow chart, methods of evaluation and allowable flaw sizes for acceptance standards and criteria, including comparisons with the ASME Code Section XI.     

Distributed parameter modeling and finite-frequency loop-shaping of electromagnetic molding machine

We derive a mathematical model for an electromagnet inside a molding machine, and propose a novel loop-shaping method of the proportional–integral (PI) controller design for the system based on the generalized KYP (GKYP) lemma. The behavior of the molding machine is difficult to capture by using finite-dimensional models owing to eddy currents spatially distributed throughout the electromagnet. To analyze fundamental properties of the system both theoretically and experimentally, we first derive a mathematical model of the machine in terms of a partial differential equation (PDE). An analysis using the PDE model shows that a low-dimensional approximation performed by standard spatial discretization results in a spillover effect, which makes the behavior of the closed-loop system oscillatory. Then, to develop an easily tunable and implementable control system, we propose a novel loop-shaping method for PI control on the basis of the GKYP lemma. In this control system design, we use multiple low-dimensional models, which work simultaneously in specified finite frequency ranges. The proposed method successfully suppresses the spillover effect despite the use of low-dimensional approximants. Finally, we show the efficiency of the proposed control design method through numerical and experimental verification and discuss a performance limitation of the PI control.     

Photocatalytic activity of TiO2 coated porous silica beads on degradation of cumene hydroperoxide

Recently, due to an increasing global concern on environmental safety, titanium dioxide (TiO₂) photocatalyst has been extensively researched for use as air and water pollution treatments. This study was initiative for producing an economically viable TiO₂ photocatalyst material with recyclability for degradation of CHP contaminated wastewater. TiO₂ P‐25, a well‐known photocatalyst, with a proper amount (15% w/w of CAC) was coated on porous silica beads (ECOLITE^®) by granulation technique, using high calcium aluminate cement (CAC) as a binder (EC+CAC+15% w/w TiO₂ P‐25). The experiments revealed that high concentration CHP solutions were completely degraded by EC+CAC+15% w/w TiO₂ P‐25 within 5 and 7 hours. The recyclability of EC+CAC+15% w/w TiO₂ P‐25 was evaluated by investigation the degradation activity of freshly prepared CHP solution under UV light irradiation using the repetitive photocatalyst beads for 6 runs. HPLC analyses indicated that the CHP degradation was completed in the 1^st run and down to over 90% in the 6^th run. Hence, EC+CAC+15% w/w TiO₂ P‐25 showed a long durability and good recyclability for CHP degradation, resulted from the good adherence of hydration product layer of CAC for TiO₂ particles as well as its large surface area that offered good adsorption for CHP.     

Apolipoprotein E epsilon 4 allele distribution in Wernicke-Korsakoff syndrome with or without global intellectual deficits

Recent genetic studies show that the apolipoprotein E (ApoE) epsilon 4 allele is a risk factor for Alzheimer's disease (AD). Whether this allele is associated with other dementing diseases is the next important question. The information could provide a clue to the pathogenetic role of ApoE. In the present study, patients with Wernicke-Korsakoff syndrome (WKS) of alcoholic etiology were divided into two groups according to the severity of intellectual deficits, i.e., those of "classical" Korsakoff patients with preserved intellectual function other than amnesia and those with global intellectual deficits. Genotyping showed that the frequency of ApoE epsilon 4 allele was significantly higher in the patients with global deficits, suggesting the involvement of this allele in the intellectual decline of WKS. In contrast, distributions of other two markers, alpha 1-antichymotrypsin and presenilin-1, did not differ between the two groups. These results added further support to the notion that the consequence of acute insult to the brain is influenced by the ApoE genotype, and suggested ApoE's role in the development of a certain group of "alcoholic dementia."     

Machine learning approach for finding business partners and building reciprocal relationships

Business development is vital for any firms. However, globalization and the rapid development of technologies have made it difficult to find appropriate business partners such as suppliers and customers, and build reciprocal relationships among them, while it simultaneously offers many opportunities. In this contribution, we propose AI-based approach to find plausible candidates of business partners using firm profiles and transactional relationships among them. We employ machine learning techniques to build a prediction model of customer–supplier relationships. We applied our approach to the large amount of actual business data. The results showed that our approach successfully found potential business partners with F-values of about 84% and reciprocity among them with F-values of about 77%. Using our method, we also developed the Web-based system that helps people in actual businesses to find their new business partners. These contribute to developing one’s own business in the complicated, specialized and rapidly changing business environments of recent years.     

Context-aware spatio-temporal event prediction via convolutional Hawkes processes

Machine Learning - Massive spatio-temporal event data sets are now available that cover events such as disease outbreaks, armed conflicts and crimes. Predicting such events and revealing the...     

System theory for numerical analysis

Many numerical schemes can be suitably studied from a system theoretic point of view. This paper studies the relationship between the two disciplines, that is, numerical analysis and system theory. We first see that various iterative solution schemes for linear and nonlinear equations can be suitably transformed into the form of a closed-loop feedback system, and show the crucial role of the internal model principle in such a context. This leads to new stability criteria for Newton's method. We then study Runge-Kutta type methods for solving differential equations, and also derive new stability criteria based on recent results on LMI. A numerical example is given to illustrate the advantage of the present theory.