Application of NASTRAN for stress analysis of left ventricle of the heart

Knowing the stress and strain distributions in the left ventricular wall of the heart is a prerequisite for the determination of the muscle elasticity and contractility in the process of assessing the functional status of the heart. NASTRAN was applied for the calculation of these stresses and strains and to help in verifying the results obtained by the computer program FEAMPS which was specifically designed for the plane-strain finite-element analysis of the left ventricular cross sections. Adopted for the analysis are the true shape and dimensions of the cross sections reconstructed from multiplanar X-ray views of a left ventricle which was surgically isolated from a dog's heart but metabolically supported to sustain its beating. A preprocessor was prepared to accommodate both FEAMPS and NASTRAN, and it has also facilitated the application of both the triangular element and isoparameteric quadrilateral element versions of NASTRAN. The stresses in several crucial regions of the left ventricular wall calculated by these two independently developed computer programs are found to be in good agreement. Such confirmation of the results is essential in the development of a method which assesses the heart performance

Faxen relations in solids - a generalized approach to particle motion in elasticity and viscoelasticity

A movable inclusion in an elastic material oscillates as a rigid body with six degrees of freedom. Displacement/rotation and force/moment tensors which express the motion of the inclusion in terms of the displacement and force at arbitrary exterior points are introduced. Using reciprocity arguments two general identities are derived relating these tensors. Applications of the identities to spherical particles provide several new results, including simple expressions for the force and moment on the particle due to plane wave excitation.Comment: 11 pages, 4 figure

Feasibility Studies on Disturbance Feedforward Techniques to Improve Wind Turbine Load Mitigation Performance: January 2009 -- January 2010

This study investigates disturbance feedforward and preview control to better understand the best possible improvement in load mitigation using advanced wind measurement techniques

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a smart grid, an example of which is energy demand forecasting. Short term energy forecasting can be used by utilities to assess if any forecasted peak energy demand would have an adverse effect on the power system transmission and distribution infrastructure. It can also help in load scheduling and demand side management. Many techniques have been proposed to forecast time series including Support Vector Machine, Artificial Neural Network and Deep Learning. In this work we use Long Short Term Memory architecture to forecast 3-day ahead energy demand across each month in the year. The results show that 3-day ahead demand can be accurately forecasted with a Mean Absolute Percentage Error of 3.15%. In addition to that, the paper proposes way to quantify the time as a feature to be used in the training phase which is shown to affect the network performance

Reduction of Tc due to Impurities in Cuprate Superconductors

In order to explain how impurities affect the unconventional superconductivity, we study non-magnetic impurity effect on the transition temperature using on-site U Hubbard model within a fluctuation exchange (FLEX) approximation. We find that in appearance, the reduction of Tc roughly coincides with the well-known Abrikosov-Gor'kov formula. This coincidence results from the cancellation between two effects; one is the reduction of attractive force due to randomness, and another is the reduction of the damping rate of quasi-particle arising from electron interaction. As another problem, we also study impurity effect on underdoped cuprate as the system showing pseudogap phenomena. To the aim, we adopt the pairing scenario for the pseudogap and discuss how pseudogap phenomena affect the reduction of Tc by impurities. We find that 'pseudogap breaking' by impurities plays the essential role in underdoped cuprate and suppresses the Tc reduction due to the superconducting (SC) fluctuation.Comment: 14 pages, 28 figures To be published in JPS

A particle system with explosions: law of large numbers for the density of particles and the blow-up time

Consider a system of independent random walks in the discrete torus with creation-annihilation of particles and possible explosion of the total number of particles in finite time. Rescaling space and rates for diffusion/creation/annihilation of particles, we obtain a stong law of large numbers for the density of particles in the supremum norm. The limiting object is a classical solution to the semilinear heat equation u_t =u_{xx} + f(u). If f(u)=u^p, 1<p \le 3, we also obtain a law of large numbers for the explosion time

Effect of local atomic and electronic structures on thermoelectric properties of chemically substituted CoSi

[[abstract]]We report the effects of Ge partial substitution for Si on local atomic and electronic structures of thermoelectric materials in binary compound cobalt monosilicides (CoSi1−xGex: 0 ≤ x ≤ 0.15). Correlations between local atomic/electronic structure and thermoelectric properties are investigated by means of X-ray absorption spectroscopy. The spectroscopic results indicate that as Ge is partially substituted onto Si sites at x ≤ 0.05, Co in CoSi1−xGex gains a certain amount of charge in its 3d orbitals. Contrarily, upon further replacing Si with Ge at x ≥ 0.05, the Co 3d orbitals start to lose some of their charge. Notably, thermopower is strongly correlated with charge redistribution in the Co 3d orbital, and the observed charge transfer between Ge and Co is responsible for the variation of Co 3d occupancy number. In addition to Seebeck coefficient, which can be modified by tailoring the Co 3d states, local lattice disorder may also be beneficial in enhancing the thermoelectric properties. Extended X-ray absorption fine structure spectrum results further demonstrate that the lattice phonons can be enhanced by Ge doping, which results in the formation of the disordered Co-Co pair. Improvements in the thermoelectric properties are interpreted based on the variation of local atomic and electronic structure induced by lattice distortion through chemical substitution.[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Nitrogen-Functionalized Graphene Nanoflakes (GNFs:N): Tunable Photoluminescence and Electronic Structures

This study investigates the strong photoluminescence (PL) and X-ray excited optical luminescence observed in nitrogen-functionalized 2D graphene nanoflakes (GNFs:N), which arise from the significantly enhanced density of states in the region of {\pi} states and the gap between {\pi} and {\pi}* states. The increase in the number of the sp2 clusters in the form of pyridine-like N-C, graphite-N-like, and the C=O bonding and the resonant energy transfer from the N and O atoms to the sp2 clusters were found to be responsible for the blue shift and the enhancement of the main PL emission feature. The enhanced PL is strongly related to the induced changes of the electronic structures and bonding properties, which were revealed by the X-ray absorption near-edge structure, X-ray emission spectroscopy, and resonance inelastic X-ray scattering. The study demonstrates that PL emission can be tailored through appropriate tuning of the nitrogen and oxygen contents in GNFs and pave the way for new optoelectronic devices.Comment: 8 pages, 6 figures (including toc figure

An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors.

To address the biological heterogeneity of lung cancer, we studied 199 lung adenocarcinomas by integrating genome-wide data on copy number alterations and gene expression with full annotation for major known somatic mutations in this cancer. This showed non-random patterns of copy number alterations significantly linked to EGFR and KRAS mutation status and to distinct clinical outcomes, and led to the discovery of a striking association of EGFR mutations with underexpression of DUSP4, a gene within a broad region of frequent single-copy loss on 8p. DUSP4 is involved in negative feedback control of EGFR signaling, and we provide functional validation for its role as a growth suppressor in EGFR-mutant lung adenocarcinoma. DUSP4 loss also associates with p16/CDKN2A deletion and defines a distinct clinical subset of lung cancer patients. Another novel observation is that of a reciprocal relationship between EGFR and LKB1 mutations. These results highlight the power of integrated genomics to identify candidate driver genes within recurrent broad regions of copy number alteration and to delineate distinct oncogenetic pathways in genetically complex common epithelial cancers