Insulating Phases Induced by Crossing of Partially Filled Landau Levels in a Si Quantum Well

We study magnetotransport in a high mobility Si two-dimensional electron system by in situ tilting of the sample relative to the magnetic field. A pronounced dip in the longitudinal resistivity is observed during the Landau level crossing process for noninteger filling factors. Together with a Hall resistivity change which exhibits the particle-hole symmetry, this indicates that electrons or holes in the relevant Landau levels become localized at the coincidence where the pseudospin-unpolarized state is expected to be stable.Comment: 4 pages, 4 figure

Well-width dependence of valley splitting in Si/SiGe quantum wells

The valley splitting in Si two-dimensional electron systems is studied using Si/SiGe single quantum wells (QWs) with different well widths. The energy gaps for 4 and 5.3 nm QWs, obtained from the temperature dependence of the longitudinal resistivity at the Landau level filling factor $\nu=1$, are much larger than those for 10 and 20 nm QWs. This is consistent with the well-width dependence of the bare valley splitting estimated from the comparison with the Zeeman splitting in the Shubnikov-de Haas oscillations.Comment: 3 pages, 2 figure

Metallic Behavior of Cyclotron Relaxation Time in Two-Dimensional Systems

Cyclotron resonance of two-dimensional electrons is studied at low temperatures down to 0.4 K for a high-mobility Si/SiGe quantum well which exhibits a metallic temperature dependence of dc resistivity $\rho$. The relaxation time $\tau_{\rm CR}$ shows a negative temperature dependence, which is similar to that of the transport scattering time $\tau_t$ obtained from $\rho$. The ratio $\tau_{\rm CR}/\tau_t$ at 0.4 K increases as the electron density $N_s$ decreases, and exceeds unity when $N_s$ approaches the critical density for the metal-insulator transition.Comment: 4 pages, 3 figure

Neural network modeling for prediction of weld bead geometry in laser microwelding

Laser microwelding has been an essential tool with a reputation of rapidity and precision for joining miniaturized metal parts. In industrial applications, an accurate prediction of weld bead geometry is required in automation systems to enhance productivity of laser microwelding. The present work was conducted to establish an intelligent algorithm to build a simplified relationship between process parameters and weld bead geometry that can be easily used to predict the weld bead geometry with a wide range of process parameters through an artificial neural network (ANN) in laser microwelding of thin steel sheet. The backpropagation with the Levenberg-Marquardt training algorithm was used to train the neural network model. The accuracy of neural network model has been tested by comparing the simulated data with actual data from the laser microwelding experiments. The predictions of the neural network model showed excellent agreement with the experimental results, indicating that the neural network model is a viable means for predicting weld bead geometry. Furthermore, a comparison was made between the neural network and mathematical model. It was found that the developed neural network model has better prediction capability compared to the regression analysis model

Thermo-mechanical analysis on thermal deformation of thin stainless steel in laser micro-welding

In the present study, a three-dimensional finite element model has been developed to simulate the temperature, stress and deformation fields in continuous wave (CW) laser micro-welding of thin stainless steel sheet. The welding deformation was experimentally evaluated using a single-mode fiber laser with a high-speed scanning system. Application of developed thermal model demonstrated that the laser parameters, such as laser power, scanning velocity and spot diameter have a significant effect on temperature field and the weld pool. In the case of welding deformation, numerical simulation was carried out by an uncoupled thermo-mechanical model. The welding stress and deformation are generated by plastic deformation during the heating and cooling periods. It was confirmed that the residual stress is higher than yield strength and has strongest effect upon the welding deformation. The numerical simulated results have proved that the developed finite element model is effective to predict thermal histories, thermally induced stresses and welding deformations in the thin material

n-3系脂肪散を強化した食事療法が有効と考えられた肺気腫の一例

An effective treatment for the advanced stages of chronic obstructive pulmonary disease (COPD) has not been established yet. We report our recent experience of one patient with pulmonary emphysema treated by dietary supplementation of n-3 fatty acid for two months. He presented improvements in clinical symptoms and pulmonary function, and suppression of leukotriene B(4) generation by peripheral leukocytes. We consequently suppose that dietary treatment with n-3 fatty acids (perilla seed oil) may offer benefits for the treatment of pulmonary emphysema by competitively inhiabiting the conversion of arachidonicacid to leukotrienes and prostanoids.今回我々は,肺気腫の症例に対してn-3系脂肪酸を強化した食事療法をおこない,臨床症状,呼吸機能検査所見ともに速やかに改善を認め,同時に白血球のロイコトリエンB4産生能が著明に減少した一例を経験したので報告する｡ 症例は67歳,男性｡主訴は労作時呼吸困難｡【第一回目入院】3カ月間入院し,薬物療法,温泉を用いた理学療法を行った｡自覚症状はやや改善が見られたが,呼吸機能検査所見の改善は得られなかった｡【第二回目入院】1年後に再入院｡n-3系脂肪酸強化食事療法も併用した｡自覚症状および,呼吸機能検査上,FVC,FEV1.0,PEFなどに改善を認めた｡n-3系脂肪酸はアラキドン酸代謝を通してロイコトリエン合成に関与すると推定されるが,経渦中に白血球のLTB4産生能の減少を認めた｡この症例は肺気腫に対するn-3系脂肪酸強化食 事療法の有用性が示唆され,病態を考える上でも興味深いと考えられた