Revisiting conditional accounting conservatism in state-controlled firms

This study explores the demand for conditional accounting conservatism from equity shareholders in state-controlled firms. An investigation of state-controlled firms listed on Hong Kong Stock Exchange from 1997 to 2013 shows that the extent of conditional conservatism in state-controlled firms increases when the leverage ratio decreases. It is also found that the high control rights held by the government in state-controlled firms are associated with high conditional conservatism. In addition, further analyses document an offsetting effect between high control rights and firm leverage; a reinforcing effect between high control rights and year of incorporation after 1992; and a substituting effect between high control rights and dividend payments. These findings suggest that the demand from equity shareholders, in addition to the debt demand, can be an important determinant of conditional conservatism and examination of these differing sources of demand can enhance the understanding on accounting conservatism in state-controlled firms

Fracture Behavior of Alumina/Monazite Multilayer Laminates

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65994/1/j.1151-2916.2000.tb01278.x.pd

SAFDet: a semi-anchor-free detector for effective detection of oriented objects in aerial images.

An oriented bounding box (OBB) is preferable over a horizontal bounding box (HBB) in accurate object detection. Most of existing works utilize a two-stage detector for locating the HBB and OBB, respectively, which have suffered from the misaligned horizontal proposals and the interference from complex backgrounds. To tackle these issues, region of interest transformer and attention models were proposed, yet they are extremely computationally intensive. To this end, we propose a semi-anchor-free detector (SAFDet) for object detection in aerial images, where a rotation-anchor-free-branch (RAFB) is used to enhance the foreground features via precisely regressing the OBB. Meanwhile, a center-prediction-module (CPM) is introduced for enhancing object localization and suppressing the background noise. Both RAFB and CPM are deployed during training, avoiding increased computational cost of inference. By evaluating on DOTA and HRSC2016 datasets, the efficacy of our approach has been fully validated for a good balance between the accuracy and computational cost

Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images.

To improve the performance of the sparse representation classification (SRC), we propose a superpixel-based feature specific sparse representation framework (SPFS-SRC) for spectral-spatial classification of hyperspectral images (HSI) at superpixel level. First, the HSI is divided into different spatial regions, each region is shape- and size-adapted and considered as a superpixel. For each superpixel, it contains a number of pixels with similar spectral characteristic. Since the utilization of multiple features in HSI classification has been proved to be an effective strategy, we have generated both spatial and spectral features for each superpixel. By assuming that all the pixels in a superpixel belongs to one certain class, a kernel SRC is introduced to the classification of HSI. In the SRC framework, we have employed a metric learning strategy to exploit the commonalities of different features. Experimental results on two popular HSI datasets have demonstrated the efficacy of our proposed methodology

Periodic sequence distribution of product ion abundances in electron capture dissociation of amphipathic peptides and proteins

The rules for product ion formation in electron capture dissociation (ECD) mass spectrometry of peptides and proteins remain unclear. Random backbone cleavage probability and the nonspecific nature of ECD toward amino acid sequence have been reported, contrary to preferential channels of fragmentation in slow heating-based tandem mass spectrometry. Here we demonstrate that for amphipathic peptides and proteins, modulation of ECD product ion abundance (PIA) along the sequence is pronounced. Moreover, because of the specific primary (and presumably secondary) structure of amphipathic peptides, PIA in ECD demonstrates a clear and reproducible periodic sequence distribution. On the one hand, the period of ECD PIA corresponds to periodic distribution of spatially separated hydrophobic and hydrophilic domains within the peptide primary sequence. On the other hand, the same period correlates with secondary structure units, such as α-helical turns, known for solution-phase structure. Based on a number of examples, we formulate a set of characteristic features for ECD of amphipathic peptides and proteins: (1) periodic distribution of PIA is observed and is reproducible in a wide range of ECD parameters and on different experimental platforms; (2) local maxima of PIA are not necessarily located near the charged site; (3) ion activation before ECD not only extends product ion sequence coverage but also preserves ion yield modulation; (4) the most efficient cleavage (e.g. global maximum of ECD PIA distribution) can be remote from the charged site; (5) the number and location of PIA maxima correlate with amino acid hydrophobicity maxima generally to within a single amino acid displacement; and (6) preferential cleavage sites follow a selected hydrogen spine in an α-helical peptide segment. Presently proposed novel insights into ECD behavior are important for advancing understanding of the ECD mechanism, particularly the role of peptide sequence on PIA. An improved ECD model could facilitate protein sequencing and improve identification of unknown proteins in proteomics technologies. In structural biology, the periodic/preferential product ion yield in ECD of α-helical structures potentially opens the way toward de novo site-specific secondary structure determination of peptides and proteins in the gas phase and its correlation with solution-phase structur

The Slope of the Near Infrared Extinction Law

We determine the slope of the near infrared extinction power law (A$_{\lambda} \propto \lambda^{-\alpha}$) for 8 regions of the Galaxy between l$\sim27^{\circ}$ and $\sim100^{\circ}$. UKIDSS Galactic Plane Survey data are compared, in colour-colour space, with Galactic population synthesis model data reddened using a series of power laws and convolved through the UKIDSS filter profiles. Monte Carlo simulations allow us to determine the best fit value of $\alpha$ and evaluate the uncertainty. All values are consistent with each other giving an average extinction power law of $\alpha$=2.14$^{+0.04}_{-0.05}$. This is much steeper than most laws previously derived in the literature from colour excess ratios, which are typically between 1.6 and 1.8. We show that this discrepancy is due to an inappropriate choice of filter wavelength in conversion from colour excess ratios to $\alpha$ and that effective rather than isophotal wavelengths are more appropriate. In addition, curved reddening tracks, which depend on spectral type and filter system, should be used instead of straight vectors.Comment: Accepted by MNRAS: 11/08/09. 13 pages, 10 figures, 2 table