Quantitative determination of cardiac glycosides in Digitalis lanata leaves by reversed-phase thin-layer chromatography

We have recently chosen to undertake a comprehensive evaluation of the modulation of gene expression by oxidative stress, using mRNA as a marker. Our model system is HA-1 hamster fibroblasts, using conditions under which we observe an adaptive response. Under these conditions, the HA-1 cells respond to a minimally toxic "pretreatment" dose of hydrogen peroxide by synthesizing RNAs and proteins that protect them against subsequent exposure to a highly cytotoxic concentration of hydrogen peroxide. Using the differential display technique to screen for modulated RNAs, we have recently reported an RNA species, adapt15/gadd7, whose steady-state level is significantly induced by a pretreatment dose of hydrogen peroxide (D. R. Crawford, G. P. Schools, S. L. Salmon, and K. J. A. Davies (1996) Arch. Biochem. Biophys. 325, 256-264). Here we report a second induced mRNA, designated adapt33. Two homologous adapt33 mRNAs were revealed by Northern blot hybridization. Both of these species were inducible by hydrogen peroxide, and they were sized at 1.46 and 0.99 kb. These inductions appeared to be dependent upon calcium, occurred as early as 90 min, and were maximal at 5 h. Cell fractionation revealed that a significant proportion of adapt33 RNA is associated with active translation. adapt33 is a novel sequence, as determined by cloning, sequencing, and GenBank analysis. adapt33 represents a new oxidant-inducible RNA and marker of cellular oxidative stress and a potential aid in the study, detection, and possible therapy of oxidant-related disorders.     

Brain-like Computing Based on Distributed Representations and Neurodynamics

A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed representations of information are processed by dynamical systems without using symbols. We present a method for such computing. We constructed an inference system using a nonmonotone neural network, which is a kind of recurrent neural network with continuous-time dynamics. This system deduces a conclusion according to state transitions of the network in which knowledge is embedded as trajectory attractors. It has the powerful ability of analogical reasoning without special treatment for exceptional knowledge. We also propose a method of linking different neurodynamical systems and show that two mutually interacting systems can process complex spatiotemporal patterns.     

Translational lemmas for DLOGTIME-uniform circuits,alternating TMs,and PRAMs

We present translational lemmas for the three standard models of parallel computation, and apply them to obtain tight hierarchy results. It is shown that, for arbitrarily small rational constant , (i) there is a language which can be accepted by a -uniform circuit family of depth and size but not by any -uniform circuit family of depth and size , (ii) there is a language which can be accepted by a -time -space ATM with l worktapes but not by any -time -space ATM with the same l worktapes if the number of tape symbols is fixed, and (iii) there is a language which can be accepted by a -time PRAM with processors but not by any -time PRAM with processors. Here, c > 0, d ≥ 1, r ₁ > 1, and r ₂ ≥ 1 are arbitrary rational constants, and l ≥ 2 is an arbitrary integer. Preliminary versions of different parts of this paper appeared in Proc. MCU 2004 (LNCS 3354) and Proc. FCT 2005 (LNCS 3623).     

Selectivity and stability via dendritic nonlinearity

Inspired by recent studies regarding dendritic computation, we constructed a recurrent neural network model incorporating dendritic lateral inhibition. Our model consists of an input layer and a neuron layer that includes excitatory cells and an inhibitory cell; this inhibitory cell is activated by the pooled activities of all the excitatory cells, and it in turn inhibits each dendritic branch of the excitatory cells that receive excitations from the input layer. Dendritic nonlinear operation consisting of branch-specifically rectified inhibition and saturation is described by imposing nonlinear transfer functions before summation over the branches. In this model with sufficiently strong recurrent excitation, on transiently presenting a stimulus that has a high correlation with feed- forward connections of one of the excitatory cells, the corresponding cell becomes highly active, and the activity is sustained after the stimulus is turned off, whereas all the other excitatory cells continue to have low activities. But on transiently presenting a stimulus that does not have high correlations with feedforward connections of any of the excitatory cells, all the excitatory cells continue to have low activities. Interestingly, such stimulus-selective sustained response is preserved for a wide range of stimulus intensity. We derive an analytical formulation of the model in the limit where individual excitatory cells have an infinite number of dendritic branches and prove the existence of an equilibrium point corresponding to such a balanced low-level activity state as observed in the simulations, whose stability depends solely on the signal-to-noise ratio of the stimulus. We propose this model as a model of stimulus selectivity equipped with self-sustainability and intensity-invariance simultaneously, which was difficult in the conventional competitive neural networks with a similar degree of complexity in their network architecture. We discuss the biological relevance of the model in a general framework of computational neuroscience.     

Using selective precipitant for uranyl ions — Fundamental studies for evaluating the precipitant performance

We have developed a simple reprocessing process for spent FBR fuels using N-cyclohexyl-2-pyrrolidone (NCP) which has selective precipitation ability for UO₂²⁺ ions. It was confirmed that NCP has sufficient precipitation ability for UO₂²⁺ ions, decontamination capability (separation of UO₂²⁺ from simulated fission products), and resistance to γ-ray radiation in nitric acid solutions. These findings indicate that NCP is applicable to our reprocessing process. We have also evaluated performances of other precipitants such as N-n-propyl-2-pyrrolidone (NProP), N-n-butyl-2-pyrrolidone (NBP), and N-n-butyl-2-pyridone (NBPyr). It was found that higher decontamination factors (DFs) are obtained by using NProP and NBP. This can be interpreted that the hydrophobicity of NProP and NBP is lower than that of NCP. Furthermore, we have obtained an experimental result that the resistance of NBPyr to γ-ray radiation is superior to that of NCP.     

Analysis of the critical heat flux in round vertical tubes under low pressure and flow oscillation conditions. Applications of artificial neural network

Artificial neural networks (ANNs) for predicting critical heat flux (CHF) under low pressure and oscillation conditions have been trained successfully for either natural circulation or forced circulation (FC) in the present study. The input parameters of the ANN are pressure, mean mass flow rate, relative amplitude, inlet subcooling, oscillation period and the ratio of the heated length to the diameter of the tube, L/D. The output is a nondimensionalized factor F, which expresses the relative CHF under oscillation conditions. Based on the trained ANN, the influences of principal parameters on F for FC were analyzed. The parametric trends of the CHF under oscillation obtained by the trained ANN are as follows: the effects of pressure below 500 kPa are complex due to the influence of other parameters. F will increase with increasing mean mass flow rate under any conditions, and will decrease generally with an increase in relative amplitude. F will decrease initially and then increase with increasing inlet subcooling. The influence curves of mean mass flow rate on F will be almost the same when the period is shorter than 5.0 s or longer than 15 s. The influence of L/D will be negligible if L/D>200. It is found that the minimum number of neurons in the hidden layer is a product of the number of neurons in the input layer and in the output layer.     

A fast and compact elimination method of empty elements from a double‐array structure

A double‐array is a well‐known data structure to implement the trie. However, the space efficiency of the double‐array degrades with the number of key deletions because the double‐array keeps empty elements produced by the key deletion. This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30–330 times faster than the conventional elimination method and maintains high space efficiency. Copyright © 2003 John Wiley & Sons, Ltd.     

Suppression of active-oxidation of Si-C fibers (Hi-Nicalon) under reduced pressure by carbon or silica coating

The suppression of the active-oxidation of Si-C fibers (Hi-Nicalon) by carbon or silica coating were investigated at 1773 K under a reduced pressure of 1.32 Pa, through mass change determination, XRD analysis, resistivity measurement, SEM observation and tensile test. The coating of carbon and silica were conducted by heat-treating at 1773 K in CO-CO₂ gas mixtures. After exposure under a reduced pressure, the carbon coating formed in pure CO gas remained almost perfect and the retained strength of 1.7 GPa was nearly identical to that in the as-heat treated state. On the other hand, the carbon coatings formed under other conditions and all the silica coatings were completely lost during vacuum exposure. The retained strengths were in the range of 0 to 1.6 GPa. The silica film was found to be ineffective for suppressing the active-oxidation during vacuum exposure.     

Layout and results from the initial operation of the high-resolution x-ray imaging crystal spectrometer on the Large Helical Device

First results of ion and electron temperature profile measurements from the x-ray imaging crystal spectrometer (XICS) diagnostic on the Large Helical Device (LHD) are presented. This diagnostic system has been operational since the beginning of the 2011 LHD experimental campaign and is the first application of the XICS diagnostic technique to helical plasma geometry. The XICS diagnostic provides measurements of ion and electron temperature profiles in LHD with a spatial resolution of 2 cm and a maximum time resolution of 5 ms (typically 20 ms). Ion temperature profiles from the XICS diagnostic are possible under conditions where charge exchange recombination spectroscopy (CXRS) is not possible (high density) or is perturbative to the plasma (low density or radio frequency heated plasmas). Measurements are made by using a spherically bent crystal to provide a spectrally resolved 1D image of the plasma from line integrated emission of helium-like Ar(16 +). The final hardware design and configuration are detailed along with the calibration procedures. Line-integrated ion and electron temperature measurements are presented, and the measurement accuracy is discussed. Finally central temperature measurements from the XICS system are compared to measurements from the Thomson scattering and CXRS systems, showing excellent agreement.     

Permeation measurements for investigating atomic hydrogen flux and wall pumping/fuelling dynamics in QUEST

In order to investigate the overall atomic hydrogen background and the dynamic characteristics of wall pumping/fuelling phenomenon, a permeation probe system has been developed and applied in the spherical tokamak QUEST. Reliability of measurements, within ±3% accuracy and a positive correlation with the hydrogen line emission over three orders of magnitude have been demonstrated for more than 3000 various plasma discharges. By comparison of the experimental permeation (flux) curves with the numerically simulated curves, the net incident atomic hydrogen flux is evaluated in the range of 1 × 10¹⁹ H m^?2 s^?1 to 4 × 10²⁰ H m^?2 s^?1. The atomic flux has been investigated as a function of various plasma operation parameters like RF power, gas pressure and magnetic configuration. Using the static particle balance and permeation measurements, the progress in wall conditioning has been investigated. An inverse correlation between the atomic hydrogen flux and improvement in wall pumping has been observed over the two campaigns.