Co (II)‐C12 alkyl carbon chain multi‐functional ionic liquid immobilized on nano‐SiO2 nano‐SiO2@CoCl3‐C12IL as an efficient cooperative catalyst for C–H activation by direct acylation of aryl halides with aldehydes

Nano‐silica supported ionic liquids composed of alkyl carbon chain and transition metal chlorides anions have been prepared and successfully applied as a heterogeneous catalyst in the direct aldehyde C‐H activation. Catalytic results indicated that nano‐SiO₂ supported ionic liquid consisting C12 alkyl carbon chain and CoCl₃ anion nano‐SiO₂@CoCl₃‐C12IL showed excellent catalytic properties with good to excellent yields towards the desired aryl ketones. The excellent recyclability of the supported catalyst, mild reaction conditions, low catalyst loading, and operational simplicity are the important features of this methodology.     

One-Step Generalized Estimating Equations With Large Cluster Sizes

Medical studies increasingly involve a large sample of independent clusters, where the cluster sizes are also large. Our motivating example from the 2010 Nationwide Inpatient Sample (NIS) has 8,001,068 patients and 1049 clusters, with average cluster size of 7627. Consistent parameter estimates can be obtained naively assuming independence, which are inefficient when the intra-cluster correlation (ICC) is high. Efficient generalized estimating equations (GEE) incorporate the ICC and sum all pairs of observations within a cluster when estimating the ICC. For the 2010 NIS, there are 92.6 billion pairs of observations, making summation of pairs computationally prohibitive. We propose a one-step GEE estimator that (1) matches the asymptotic efficiency of the fully iterated GEE; (2) uses a simpler formula to estimate the ICC that avoids summing over all pairs; and (3) completely avoids matrix multiplications and inversions. These three features make the proposed estimator much less computationally intensive, especially with large cluster sizes. A unique contribution of this article is that it expresses the GEE estimating equations incorporating the ICC as a simple sum of vectors and scalars.     

Stabilization of zeylenone in rat plasma by the presence of esterase inhibitors and its LC‐MS/MS assay for pharmacokinetic study

Six esterase inhibitors, namely EDTA·2Na⁺, NaF, phenylmethanesulfonyl fluoride, dichlorvos, bis‐nitrophenyl phosphate (BNPP) and thenoyltrifluoroacetone, and the mixture of NaF and BNPP, were evaluated for the stabilization of labile benzoate containing zeylenone in rat plasma. The mixture appeared to exhibit the most effectively stabilizing effect with the degraded content of zeylenone decreasing from >60% (in the absence of inhibitors) to <6%. Following the stabilization by the addition of NaF (5 mm ) and BNPP (5 mm ), the analytes in rat plasma were acidified by formic acid and extracted into ethyl acetate at 0°C. After chromatographic separation, the detection of zeylenone was performed on a 3200 Q‐Trap with positive ion electrospray mode, monitoring the ion transition m/z 383.2 → 105.0. The method was validated over the range from 2.68 to 1340 ng/mL with inter‐ and intra‐run precision for the quality control samples being less than 6.8%. The assay accuracy was within 100 ± 7.0%. The validated method was successfully applied to a pharmacokinetic study in rats after the intratracheal administration of zeylenone in free drug or polymeric micellar solutions. The results showed that the pulmonary absorption of zeylenone loaded in micelles was significantly retarded compared with that of free drug solutions. Copyright © 2012 John Wiley & Sons, Ltd.     

Four forbidden subgraph pairs for hamiltonicity of 3-connected graphs

Acta Mathematicae Applicatae Sinica, English Series - For non-negative integers i, j and k, we denote the generalized net as N i,j,k , which is a triangle with disjoint paths of length i, j and k,...     

Co-channel Speech Separation Based on Amplitude Modulation Spectrum Analysis

A lot of effort has been made to achieve co-channel (two-talker) speech separation. However, the comprehensive analysis of the amplitude modulation spectrum (AMS) to address this problem has received little attention. In this paper, we propose an approach to exploit the AMS and to perform the separation based on the framework of computational auditory scene analysis (CASA). Specifically, this method utilizes the periodicity encoded in the AMS and then makes the channel selection. The main features of the approach are: (1) the reassignment method is used to improve the spectral resolution of the AMS in short duration; (2) a template-based pitch detector is used to determine the dominant fundamental frequency (F0) in an individual channel; (3) segmentation and grouping, the two stages in the CASA-based approaches, are employed to increase the robustness of channel selection. Systematic evaluation and comparison show that the proposed approach yields better performance than the previous system.