Bankruptcy prediction is a key part in corporate credit risk management. Traditional bankruptcy prediction models employ financial ratios or market prices to predict bankruptcy or financial distress prior to its occurrence. We investigate the predictive accuracy of corporate efficiency measures along with standard financial ratios in predicting corporate distress in Chinese companies. Data Envelopment Analysis (DEA) is used to measure corporate efficiency.In contrast to previous applications of DEA in credit risk modelling where it was used to generate a single efficiency -Technical Efficiency, we assume Variable Returns to Scale, and decompose Technical Efficiency into Pure Technical Efficiency and Scale Efficiency. These measures are introduced into Logistic Regression to predict the probability of distress, along with the levels of Returns to Scale. Effects of efficiency variables are allowed to vary across industries through the use of interaction terms, whilst the financial ratios are assumed to have the same effects across all sectors. The results show that the predictive power is improved by this corporate efficiency information.

For the management of coal fly ashes (CFAs) from coal-fired power plants (CFPPs), characterization of PAHs and PCBs in CFAs is imperative. The 18 PAH and 86 PCB congeners in CFAs collected from 18 large-scale CFPPs in China were detected using GC/MS system. The PAH concentrations were in the range of 5.51-70.9 ng g -1 for 16 CFPPs with individual block power capacity as 600 MW (IBPC-600), significantly lower than 886-916 ng g -1 for 2 CFPPs with IBPC as 200 and 300 MW (IBPC-200/300). Both PAH and PCB congeners for 18 CFPPs were dominated by low molecular weight ones. The 3-and 2-ring PAHs, di-, tri-and tetra-PCBs were the predominant homologs. PAH profiles for 16 CFPPs with IBPC-600 were significantly different from other industrial stacks based on higher coefficients of divergence. The BaP-based toxic equivalency (BaPeq) concentration and BaP-based equivalent carcinogenic power (BaPE) for 16 CFPPs with IBPC-600 were 0.834 ng g -1 and 0.570, much lower than corresponding 20.5 ng g -1 and 15.4 for 2 CFPPs with IBPC-200/300. No difference existed for Σ 86 PCBs between CPFFs with IBPC-600 and -200/300, which ranged from 9.60 to 32.1 ng g -1 . Higher mean carcinogenic PAH concentrations for 2 CFPPs with IBPC-200/300 and PCBs-TEQ concentration for 18 CFPPs indicated the application of CFAs as soil amendment should be prohibited. The PAH concentrations for 18 CFPPs were well correlated with the total organic carbon (TOC) values, while PCB concentrations showed not this trend, indicated the different formation mechanism between PCBs and PAHs.

Purpose: The bid-ask spread is important for many reasons. Because spread data are not always available, many methods have been suggested for estimating the spread. Existing papers focus on the performance of the estimators either under ideal conditions or in real data. The gap between ideal conditions and the properties of real data is usually ignored. The consistency of the estimates across various sampling frequencies is also ignored. This paper investigates the performance of estimators of the bid-ask spread in a wide range of circumstances and sampling frequencies. Design:The estimators and the possible errors are analysed theoretically. Then we perform simulation experiments, reporting the bias, standard deviation and root mean square estimation error of each estimator. More specifically, we assess the effects of the following factors on the performance of the estimators: the magnitude of the spread relative to returns volatility, randomly varying of spreads, the autocorrelation of mid-price returns, and mid-price changes caused by trade directions and feedback trading. 1 the sampling frequency. In small samples, the standard deviation can be more important to the estimation error than bias; in large samples, the opposite tends to be true. Originality:There is a conspicuous lack of simulation evidence on the comparative performance of different estimators of the spread under the less than ideal conditions that are typical of real-world data. This paper aims to fill this gap.

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A new estimator of bid-ask spreads is presented. When the trade direction is known, any estimate of the spread is associated with a unique series of conjectural midprices derived by adjusting the observed transaction price by half the estimated spread. It is shown that the covariance of successive conjectural mid-price returns is maximised (or least negative) when the estimated spread is equal to the true spread. A search procedure to maximise this covariance may therefore be used to estimate the true spread. The performance of this estimator under various conditions is examined both theoretically and with Monte Carlo simulations. The simulations confirm the theoretical results. The performance of the estimator is good.

Summary Rejection inference aims to reduce sample bias and to improve model performance in credit scoring. We propose a semisupervised clustering approach as a new rejection inference technique. K‐prototype clustering can deal with mixed types of numeric and categorical characteristics, which are common in consumer credit data. We identify homogeneous acceptances and rejections and assign labels to part of the rejections according to the label of acceptances. We test the performance of various rejection inference methods in logit, support vector machine and random‐forests models based on data sets of real consumer loans. The predictions of clustering rejection inference show advantages over other traditional rejection inference methods. Inferring the label of the rejection from semisupervised clustering is found to help to mitigate the sample bias problem and to improve the predictive accuracy.

Different stent structures lead to different deformations of blood vessels, such as different cross-sectional shapes, which further influence the blood flow patterns. In this paper, six non-commercial stents with different link structures called I-, C-, S-, U-, N- and W-types were considered. Their influences on arteries with five different curvatures (i.e., 0[Formula: see text], 15[Formula: see text], 30[Formula: see text], 45[Formula: see text] and 60[Formula: see text]) were studied using finite element method. Four indices including the maximum plastic strain of stents, the rate of expansion, the maximum von Mises stress and the ellipticity of arteries, were compared for all cases. The results showed that the S-type or U-type stents, with larger plastic strain and lower von Mises stress on the arteries, provided the optimal outcome. As the link structures became complex, the arterial expansion increased monotonically, while the ellipticity of arteries showed a decreasing tendency in the vessel models. The present study could be useful for the commercial design and clinic selection of a stent with different link structures for different curved arteries.

45S5 bioactive glass (BG) scaffolds show great potential in bone tissue engineering due to their superior osteoinductivity and osteoconductivity. However, such scaffolds generally possess poor mechanical properties. Here, inspired by the reinforcing principle of confined concrete elements in civil engineering, poly caprolactone (PCL)/polyethylene glycol (PEG) film-wrapped 45S5 BG scaffolds were prepared by gluing highly porous foam-replicated BG scaffolds and electrospun PCL/PEG films together with a PCL layer. The results showed that the compressive strength of the PCL/PEG film-wrapped scaffolds was greatly improved, compared to that of unwrapped BG scaffolds. Moreover, the PCL/PEG film exhibited hydrophilicity, responsible for improved cell activity with respect to the hydrophobic PCL one. Thus, the present work introduces a convenient approach to improve the mechanical properties of highly porous bioceramic scaffolds, and is relevant for future robust scaffold design. K E Y W O R D S45S5 bioactive glass scaffold, bone tissue engineering, electrospinning, mechanical properties, poly caprolactone/polyethylene glycol film