High-performance self-aligned SiGeC HBT with selectively grown Si/sub 1-x-y/Ge/sub x/C/sub y/ base by UHV/CVD

Si/sub 1-x-y/Ge/sub x/C/sub y/ selective epitaxial growth (SEG) was performed by cold-wall, ultrahigh-vacuum chemical vapor deposition, and the effects of incorporating C on the crystallinity of Si/sub 1-x-y/Ge/sub x/C/sub y/ layers and the performance of a self-aligned SiGeC heterojunction bipolar transistor (HBT) were evaluated. A Si/sub 1-x-y/Ge/sub x/C/sub y/ layer with good crystallinity was obtained by optimizing the growth conditions. Device performance was significantly improved by incorporating C, as a result of applying Si/sub 1-x-y/Ge/sub x/C/sub y/ SEG to form the base of a self-aligned HBT. Fluctuations in device performance were suppressed by alleviating the lattice strain. Furthermore, since the B out diffusion could be suppressed by incorporating C, the cutoff frequency was able to be increased with almost the same base resistance. A maximum oscillation frequency of 174 GHz and an emitter coupled logic gate-delay time of 5.65 ps were obtained at a C content of 0.4%, which shows promise for future ultrahigh-speed communication systems.     

Graphite formation on Ni film by chemical vapor deposition

Thin film formation of graphite by chemical vapor deposition using 2-methyl-1,2′-naphthyl ketone as a starting material was carried out on Ni film substrates. On Ni films directly deposited on quartz glass, the graphite films were obtained when the Ni film thickness was above 1 000 Å and above 5 000 Å at 700 °C and 1 000 °C, respectively. Depositions on thinner Ni film substrates comprise amorphous carbon (a-C) or graphite tubes which was owing to the thermal coagulation of the Ni film into droplets. On the other hand, graphite film was obtained on the Ni film with thickness 10 Å when a-C was inserted between the Ni film and the quartz glass. The coagulation of the Ni film is considered to be avoided by inserting a-C layer.     

Rates for intramolecular excimer formation of poly(α-methylstyrene) measured by using picosecond pulse radiolysis

Summary The rate constants for intramolecular excimer formation, k_DM, of poly(α-methylstyrene) with different molecular weight were determined by using picosecond pulse radiolysis. Values of k_DM for poly(α-methylstyrene) are a little smaller than those for polystyrene with nearly same molecular weight. It appears to be mainly due to steric hindrance by methyl substituent of main chain.     

Screening of Inhibitors Targeting Heat Shock Protein 47 Involved in the Development of Idiopathic Pulmonary Fibrosis

Heat shock protein 47 (HSP47), a collagen-specific molecular chaperone, is causally related to fibrotic diseases, including idiopathic pulmonary fibrosis. The identification of Compounds that interfere with the HSP47-collagen interaction is essential for the development of relevant therapeutics. Herein, we prepared human HSP47 as a soluble fusion protein expressed in E. coli and established an assay system for HSP47 inhibitor screening. We screened a natural and synthetic Compound library established at Nagasaki University. Among 1023 Compounds, 13 exhibited inhibitory activity against human HSP47, of which three inhibited its function in a dose-dependent manner. Epigallocatechin-3-O-gallate, one of these three Compounds, is a typical polyphenol Compound derived from tea leaves. Structurally related Compounds were synthesized and examined for their activity, revealing a hydroxyl group at A-ring position 5 as important for its activity. The present findings provide valuable insight for the development of natural product-derived therapeutics for fibrotic diseases, including idiopathic pulmonary fibrosis.     

Lysozyme requires fluctuation of the active site for the manifestation of activity

Mutations around His15 which lie far away from the active site,stimulated glycol chitin activity of lysozyme at physiologicaltemperature. Del-Argl4Hisl5 lysozyme, a mutant lysozyme whoseArgl4 and Hisl5 were deleted together, and has the highest activityamong these mutant lysozymes, had a similar binding abilityto a trimer of N-acetyl-glucosamine, a substrate analogue, relativeto native lysozyme. This suggests that the increased activitywas due to an increased k_cat in the catalysis reaction. TheH-D exchange rate of the N-1 proton in the Trp63 which is locatedin the active site cleft, was enhanced in the Del-Argl4Hisl5lysozyme, while 2-D proton NMR analysis revealed no conformationalchange around Trp63. We conclude that some sort of fluctuationat the active site might be required for the manifestation ofactivity. This theory is supported by the finding that the Del-Argl4Hisl5lysozyme showed a shift in temperature dependency of activityto lower temperatures compared with that of native lysozyme.     

Isolation kernel: the X factor in efficient and effective large scale online kernel learning

Large scale online kernel learning aims to build an efficient and scalable kernel-based predictive model incrementally from a sequence of potentially infinite data points. Current state-of-the-art large scale online kernel learning focuses on improving efficiency. Two key approaches to gain efficiency through approximation are (1) limiting the number of support vectors, and (2) using an approximate feature map. They often employ a kernel with a feature map with intractable dimensionality. While these approaches can deal with large scale datasets efficiently, this outcome is achieved by compromising predictive accuracy because of the approximation. We offer an alternative approach that puts the kernel used at the heart of the approach. It focuses on creating a sparse and finite-dimensional feature map of a kernel called Isolation Kernel. Using this new approach, to achieve the above aim of large scale online kernel learning becomes extremely simple—simply use Isolation Kernel instead of a kernel having a feature map with intractable dimensionality. We show that, using Isolation Kernel, large scale online kernel learning can be achieved efficiently without sacrificing accuracy.

     

Detection of a brain aneurysm and a way to search for a brain aneurysm aimed at the development of a system to simulate an operation

In this article, a system is proposed for a simulated operation which would help a trainee surgeon to perform a medical operation to ensure that a cerebral aneurysm does not burst. The physician will have acquired empirical medical technologies from operations in traditional clinical teaching. However, there is a problem with safety and the burden to the patient. Therefore, recently a new training approach for a simulated medical operation using virtual reality has been explored. With the aim of developing a simulated system for a medical operation for a cerebral aneurysm, we considered the necessary functions such as detecting the brain aneurysm that is the target of the operation, and searching for a suitable blood vessel to make a plan for the operation.     

Shear viscosity of the B phase of superfluid3He

The shear viscosity (T) in the Balian-Werthamer (BW) state of superfluid ³ He is calculated variationally throughout the region 0t 1(t=T/T _c) from the transport equation for Bogoliubov quasiparticles. Coherence factors are treated exactly in the calculation of the collision integral. The numerical result for =_s= _s(T)/_n(T_c) agree very well with experiment in the range 0.8t1.0. Analytic expressions = 0.577 (1–1.0008t) and =1–(23/64) [=(T)/k _B T] are obtained in the low-temperature region and in the vicinity ofT _c, respectively. From the numerical analysis it is shown that the latter equation is valid only in the temperature range 0.9997t1.0.Supported by the Research Institute for Fundamental Physics, Kyoto University.     

Dominant stress region for crack initiation at interface edge of microdot on a substrate

In order to examine the mechanics of crack initiation at the free interface edge of a microcomponent on a substrate, delamination tests are carried out for two specimen shapes of Cr microdots on a SiO₂ substrate. The microdots of the first specimen are shaped like the frustum of a round cone. The Cr microdots are successfully delaminated from the SiO₂ substrate in a brittle manner and the critical load is measured by atomic force microscopy (AFM) with a lateral loading apparatus. Stress analysis reveals that a singular stress field exists near the interface edge and the strength for the crack initiation is governed by the intensified normal stress field. The critical stress intensity parameter is evaluated as K_σC ≈ 0.24 MPa m^0.39. Similar delamination tests are conducted for microdots shaped like the frustum of an oval cone. The stress distributions at the crack initiation of this specimen shape show a higher normal stress than the first specimen shape in the region near the interface edge of about x < 40 nm, while it is lower in the region of about x > 50 nm (x: distance from the edge). This suggests a limitation of conventional fracture mechanics: namely, the crack initiation in these specimens is not uniquely governed by the intensity of the singular field. It is found that the delamination crack is initiated when the averaged stress σ_ya in the region of 90-130 nm reaches 190-270 MPa, regardless of the specimen shape. This indicates that the dominant stress region of crack initiation is roughly estimated as 90-130 nm and the criterion is given in terms of the averaged stress in the region.     

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.