Analysis of PD-generated SF/sub 6/ decomposition gases adsorbed on carbon nanotubes

Chemical byproducts analysis has been recognized as a powerful diagnosis method for SF₆ gas-insulated switchgear (GIS). The authors have previously demonstrated that a carbon nanotube (CNT) gas sensor could detect partial discharge (PD) generated in SF₆ gas. However, PD-generated decomposition gas species, which were responsible for the CNT gas sensor response, have not been identified yet. In this paper, two kinds of experiments were conducted in order to identify the responsible decomposition gas species. At first, the decomposition gas molecules adsorbed on CNTs were analyzed by Fourier transformation infrared (FTIR) spectroscopy. FTIR absorbance was observed around 735 cm^-1 after CNTs were exposed to PD generated in SF₆. In the second experiment, the CNT gas sensor responses to typical SF₆ decomposition products (HF and SF₄) were examined. The CNT gas sensor responded to these gases in the same way as to PD generated in SF₆. SF₄ response was larger than HF response. Based on these results, SF ₄ and SOF₂ emerged as candidates for the responsible decomposition gases. Electrochemical interactions between adsorbed gas molecules and CNT were discussed based on theoretical predictions of molecular orbital calculations. The calculation results suggested that both of SOF₂ and SF₄ could increase the CNT gas sensor conductance     

Impurity effect on Kramer-Pesch core shrinkage ins-wave vortex and chiralp-wave vortex

The low-temperature shrinking of the vortex core (Kramer-Pesch effect) is studied for an isolated single vortex for chiral p-wave and s-wave superconducting phases. The effect of nonmagnetic impurities on the vortex core radius is numerically investigated in the Born limit by means of a quasiclassical approach. It is shown that in the chiral p-wave phase the Kramer-Pesch effect displays a certain robustness against impurities owing to a specific quantum effect, while the s-wave phase reacts more sensitively to impurity scattering. This suggests chiral p-wave superconductors as promising candidates for the experimental observation of the Kramer-Pesch effect.     

Work-time optimal k-merge algorithms on the PRAM

For 2⩽k⩽n, the k-merge problem is to merge a collection of ksorted sequences of total length n into a new sorted sequence. The k-merge problem is fundamental as it provides a common generalization of both merging and sorting. The main contribution of this work is to give simple and intuitive work-time optimal algorithms for the k-merge problem on three PRAM models, thus settling the status of the k-merge problem. We first prove that Ω(n log k) work is required to solve the k-merge problem on the PRAM models. We then show that the EREW-PRAM and both the CREW-PRAM and the CRCW require Ω(log n) time and Ω(log log n+log k) time, respectively, provided that the amount of work is bounded by O(n log k). Our first k-merge algorithm runs in Θ(log n) time and performs Θ(n log k) work on the EREW-PRAM. Finally, we design a work-time optimal CREW-PRAM k-merge algorithm that runs in Θ(log log n+log k) time and performs Θ(n log k) work. This latter algorithm is also work-time optimal on the CREW-PRAM model. Our algorithms completely settle the status of the k-merge problem on the three main PRAM models     

HSPF Simulation of Runoff and Sediment Loads in the Upper Changjiang River Basin, China

To evaluate the performance of a computer model simulating runoff and sediment load in the upper region of the Changjiang (Yangtze River) basin over a relatively short time interval, including examining the applicability of the input precipitation data generated from global circulation models and satellite data, we used a spatially distributed model, HSPF with the International Satellite Land Surface Climatology Project (ISLSCP) precipitation data for 1987 and 1988 as input data. The Nash–Sutcliffe coefficient (R2) for 5-day average streamflow was 0.94 in the calibration period and 0.95 in the verification period for the whole upper region. Moreover, the model simulated the 5-day average streamflow well in each main tributary, as shown by R2 values of 0.46–0.96, except that it underestimated the peak flow rates during the flood season over 2 years by up to 71% in Tuojiang and 61% in Jialingjiang. The model simulated the 5-day concentrations of suspended solids (SS) fairly well in the headwaters and upper regions of the Jinshajiang, Yalongjiang, and Minjiang watersheds, as shown by R2 values of 0.31–0.65. In the other regions, however, the model underestimated the SS load by up to 72%, and rarely simulated the fluctuation of SS concentration in each river channel during the flood season. These errors led to the underestimation of sediment runoff volume from the whole upper region during the flood season, as shown by the ratio of the simulated sediment load to the observed data at Yichang: 0.69 in the calibration period and 0.68 in the verification period. The ISLSCP precipitation tended to be more frequent and less intense than the measured precipitation. This was probably the main reason why the HSPF did not perform well in all regions at all times.     

Some Notes on Stability Problems of Probabilistic Automata

Abstract

The behavior of a probabilistic automaton is essentially characterized by products of matrices selected from a given finite set of stochastic matrices. It is of interest to know under what conditions these matrix products are stable against perturbations of the entries in the matrices.     

A Brief Survey of Asymmetric MDS and Some Open Problems

Behaviormetrika - A brief review is made of a body of extant asymmetric MDS models and methods, given a one-mode, two-way asymmetric square relational data matrix whose elements are similarity or...     

The isothermal conductivity improvement in zirconia-based ceramics under 24 GHz microwave heating

Abstract Under 24-GHz millimetre-wave irradiation heating ionic conductivity of zirconia base ceramics was up to 20 times higher than that of a conventionally-heated sample at the same temperature of 400 °C. The degree of enhancement could be altered by changing the stabilising atom from Y to Yb. Enhancement of ionic conduction was prominent in the setup condition of larger self-heating ratio and larger MMW absorbing materials. The isothermal improvement of ionic conductivity under MMW irradiation would be ascribed to the non-thermal effect.     

Impact of Serum Chemerin Levels on Liver Functional Reserves and Platelet Counts in Patients with Hepatocellular Carcinoma

Obesity-related metabolic abnormalities, including adipokine imbalance and chronic inflammation, are involved in liver carcinogenesis. Chemerin, a novel adipokine, plays a critical role in adipogenesis, energy metabolism, and inflammation. We evaluated the impact of serum chemerin levels on liver functional reserves in hepatocellular carcinoma (HCC) patients and on the recurrence and prognosis of HCC. This study included 44 patients with any stage of HCC who underwent curative treatment at Gifu Municipal Hospital (Gifu, Japan) between 2006 and 2007. Recurrence-free survival and overall survival were estimated using the Kaplan-Meier method. Serum albumin levels (Pearson’s correlation coefficient; r = 0.3110, p = 0.0399), platelet counts (r = 0.4159, p = 0.0050), and prothrombin times (r = 0.3775, p = 0.0115) were significantly correlated with serum chemerin levels in patients with HCC, and they were inversely correlated with Child-Pugh scores (r = −0.3732, p = 0.0126), serum alanine aminotransferase levels (r = −0.3864, p = 0.0105), and total bilirubin levels (r = −0.4023, p = 0.0068). Among these variables, a multiple comparison test identified that platelet counts and total bilirubin levels were associated with serum chemerin levels (p < 0.0083). No significant correlation was found between serum chemerin levels and recurrence-free survival (p = 0.3691) or overall survival (p = 0.7916). In HCC patients, serum chemerin concentrations were correlated with liver functional reserves and platelet counts, but not with recurrence or prognosis.     

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes.

Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10?kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation.

Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors.

Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.