Direct x-ray imaging system using an amplified metal-oxide-semiconductor imager in the 4-13-nm wavelength region

We describe a direct x-ray imaging system that uses an amplified metal-oxide-semiconductor imager to detect soft x rays directly for real-time imaging. From the absolute sensitivity of this system as measured through the use of a monochromatic synchrotron radiation beam and a GaAsP Schottky-type photodiode, the minimum sensitivity at a wavelength of 13 nm was estimated to be greater than 10(8)photons mm(-2). This is sufficient to detect soft x rays directly for real-time imaging. Onion cell observations at wavelengths of 4.3 and 4.6 nm indicate that x-ray absorption by the carbon in the cells was detected. This is a promising imaging system for the soft x-ray region in which conventional CCD's are difficult to use.     

Theoretical analysis of the spatial phase-matching loci for second-harmonic generation and multiwave-mixing interactions

We report a theoretical analysis on spatial noncolinear phase matching of multiwave mixing and its application to a second-harmonic-generation (SHG) experiment. From the numeric calculations, the noncolinear phase-matching properties in general situations were determined. The theory gives the applicability for all noncolinear phase matching. Fine coincidences between theoretical calculations and observed spatial loci on noncollinear phase-matching SHG were confirmed. Relations that allow the calculation of the noncollinear phase-matching angle for any case of SHG are established. As an example, the noncolinear phase-matched SHG pattern on a screen is calculated numerically in the case of SHG of 1064 nm from a Nd:YAG laser under the phase-matched condition for two organic nonlinear crystals: 1-(2-thienyl)-3-(4-methyphenyl) propene-1 (TC-28), which is biaxial, and (2-furyl) methacrylic anhydride (FMA), which is uniaxial. Experimental results compared quite favorably with the theoretical analysis. Noncolinear phase matching may be of great practical interest in optical multiwave-mixing processes, such as optical parametric oscillation and optical parametric amplification. This technique also can be used for the measurement of crystal optical constants.     

Some properties of mullite powders prepared by chemical vapour deposition

The sinterability of mullite (3Al₂O₃·2SiO₂) powder prepared by chemical vapour deposition was examined to improve the conditions for fabricating dense mullite ceramics. The starting powder contained not only mullite, but also a small amount of -Al₂O₃ (Al-Si spinel) and amorphous material. Although the compressed powder was fired at a temperature between 1550 and 1700 °C for 1, 3 and 5 h, the relative densities of the sintered compacts were limited to 90%: (i) due to the creation of pores/microcracks during the solid state reaction (1100–1350 °C), and (ii) due to restriction on the rearrangement of grains because the amount of liquid phase (1550–1700 °C) was insufficient. Calcination of the starting powder was effective for preparation of easily sinterable powder with homogeneous composition. When the compact formed by compressing the calcined powder at 1400 °C for 1 h was fired at 1650 °C for 3 h, the relative density was raised up to 97.2%; moreover, mullite was the only phase detected from the sintered compact. The sintered compact was composed of polyhedral grains with sizes of 1–2 m and elongated grains with long axes of 6 m.     

Practical Reliability and Maintainability Analysis Tool for an Open Source Cloud Computing

We focus on a cloud computing environment by using open source softwares such as OpenStack and Eucalyptus because of the unification management of data and low cost. A cloud computing is attracting attention as a network service to share the computing resources, that is, networks, servers, storage, applications, and services. We propose jump diffusion models based on stochastic differential equations in order to consider the interesting aspect of the provisioning process. Especially, the reliability and maintainability analysis tool for cloud computing is developed in this paper. Also, we analyze actual data to show numerical illustrations of application of the software analysis tool considering the characteristics of cloud computing. Copyright © 2015 John Wiley & Sons, Ltd.     

Cu-NMR study on high-T c cuprate La1.89Ca1.11Cu2O6+δ (La2126)

Cu-NMR spectra and the nuclear spin-lattice relaxation rate T ₁ ^-1 have been studied intensively on the bilayer type high-T_c cuprate La_1.89Ca_1.11Cu₂O₆₊ (La2126). The resonance line shift showed a monotonic decrease with lowering temperature in the normal state, indicating that this compound belongs to the lightly-doped region. The Curie-Weiss temperature dependence of (T₁T)^–1 in the normal state shows that the pseudo spin-gap does not always exist in the light-doped bilayer systems.     

Estimation of time-dependent input from neuronal membrane potential

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For that purpose, the membrane potential dynamics must be specified. We consider the Ornstein-Uhlenbeck stochastic process, one of the most common single-neuron models, with time-dependent mean and variance. Assuming the slow variation of these two moments, it is possible to formulate the estimation problem by using a state-space model. We develop an algorithm that estimates the paths of the mean and variance of the input current by using the empirical Bayes approach. Then the input firing rates are directly available from the moments. The proposed method is applied to three simulated data examples: constant signal, sinusoidally modulated signal, and constant signal with a jump. For the constant signal, the estimation performance of the method is comparable to that of the traditionally applied maximum likelihood method. Further, the proposed method accurately estimates both continuous and discontinuous time-variable signals. In the case of the signal with a jump, which does not satisfy the assumption of slow variability, the robustness of the method is verified. It can be concluded that the method provides reliable estimates of the total input firing rates, which are not experimentally measurable.     

Optimizing time histograms for non-Poissonian spike trains

The time histogram is a fundamental tool for representing the inhomogeneous density of event occurrences such as neuronal firings. The shape of a histogram critically depends on the size of the bins that partition the time axis. In most neurophysiological studies, however, researchers have arbitrarily selected the bin size when analyzing fluctuations in neuronal activity. A rigorous method for selecting the appropriate bin size was recently derived so that the mean integrated squared error between the time histogram and the unknown underlying rate is minimized (Shimazaki & Shinomoto, 2007 ). This derivation assumes that spikes are independently drawn from a given rate. However, in practice, biological neurons express non-Poissonian features in their firing patterns, such that the spike occurrence depends on the preceding spikes, which inevitably deteriorate the optimization. In this letter, we revise the method for selecting the bin size by considering the possible non-Poissonian features. Improvement in the goodness of fit of the time histogram is assessed and confirmed by numerically simulated non-Poissonian spike trains derived from the given fluctuating rate. For some experimental data, the revised algorithm transforms the shape of the time histogram from the Poissonian optimization method.     

Peroxiredoxin 2 as a chemotherapy responsiveness biomarker candidate in osteosarcoma revealed by proteomics

Purpose : We aimed to identify novel chemotherapy responsiveness biomarkers for osteosarcoma (OS) by investigating the global protein expression profile of 12 biopsy samples from OS patients. Experimental design : Six patients were classified as good responders and six as poor responders, according to the Huvos grading system. The protein expression profiles obtained by 2‐D DIGE consisted of 2250 protein spots. Results : Among them, we identified 55 protein spots whose intensity was significantly different (Bonferroni adjusted p‐value<0.01) between the two patient groups. Mass spectrometric protein identification demonstrated that the 55 spots corresponded to 38 distinct gene products including peroxiredoxin 2 (PRDX 2). Use of a specific antibody against PRDX 2 confirmed the differential expression of PRDX 2 between good and poor responders, while PRDX 2 levels as measured by Western blotting correlated highly with their corresponding 2‐D DIGE values. The predictive value of PRDX 2 expression was further confirmed by examining an additional four OS cases using Western blotting. Conclusions and clinical relevance : These results establish PRDX 2 as a candidate for chemotherapy responsiveness marker in OS. Measuring PRDX 2 in biopsy samples before treatment may contribute to more effective management of OS.     

Extremely localized interaction in a market model

The model of self-organized criticality (SOC) is a useful tool to understand the complexity of natural systems in the form of the artificial life and the artificial market. However, SOC remains the question what guarantees the criticality even though the natural systems seem to keep itself in the critical state. In this paper, we focus on the locality of interaction in zero-intelligence plus (ZIP) model. The extremely localized interaction changes the behavior of the ZIP model from equilibrium to intermittency. Although the original ZIP model falls into unstable with some noise, extremely localized interaction model archives robust intermittency against the noise parameter. Further, the statistical property of intermittent behavior shows the power-law nature.     

A study on a quantum-inspired evolutionary algorithm based on pair swap

A quantum-inspired evolutionary algorithm (QEA) is proposed as a stochastic algorithm to perform combinatorial optimization problems. The QEA is evolutionary computation that uses quantum bits and superposition states in quantum computation. Although the QEA is a coarse-grained parallel algorithm, it involves many parameters that must be adjusted manually. This paper proposes a new method, named pair swap, which exchanges each best solution information between two individuals instead of migration in the QEA. Experimental results show that our proposed method is a simpler algorithm and can find a high quality solution in the 0-1 knapsack problem. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007