A Comparison of Six DIF Detection Methods

In the context of educational measurement, a test item is identified as differentially functioning across groups when the probability an examinee’s response to it depends on group membership. Methods for detecting uniform and nonuniform DIF have been studied and examined over decades to improve the validity of tests. The current study focused on examining and comparing the effectiveness of six DIF detection methods: the Mantel-Haenszel (MH) procedure, the Logistic Regression procedure, the multiple indicators multiple causes (MIMIC) model, the item response theory likelihood-ratio test (IRT-LR), Lord’s IRT-based Wald test and a Randomization Test based on a R-square change statistic. A simulation study was conducted in which the factors manipulated were the percentage of DIF items (%DIF), sample size (number of examinees in each group), test length (number of items in test), type and magnitude of DIF, and the mean ability difference between groups of examinees. The results showed that the MIMIC model had the greatest power in detecting uniform DIF items, as well as nonuniform DIF items with longer tests. The logistic regression method and the randomization test are quite efficient in detecting uniform DIF items, but the randomization test only applies when the two groups of people have the same mean ability. The IRT methods are more useful for detecting nonuniform DIF items. The percentage of DIF items does not have much effect on the power of each method, while most methods are better when detecting large magnitude DIF than small, and are better when the sample size for each group is large

Moral Hazard Effects of Corporate Bond Guarantee Purchases: Empirical Evidence from China

This study examines corporate bond guarantees by developing a theoretical model that decomposes the overall impact of a guarantee into signalling and incentive effects and presenting empirical evidence based on data from China’s corporate bond market. Our empirical research yields considerable evidence for the effects we posit in the model and provides some important insights into the problems of adverse selection and moral hazard in China’s bond market. The empirical evidence shows that the bond issuer with lower credit rating are more willing to purchase a bond guarantee and guaranteed bonds have a higher issue spread yield than those non-guaranteed bonds, even though both have the same bond credit rating. Our findings suggest that moral hazard would be better than adverse selection to explain the self- selection of bond guarantees. Prior to bond issuance credit rating signal provides a mechanism to mitigate information inequality, while bond guarantees relieve information asymmetry afterwards.&nbsp

Quantum criticality driven by the cavity coupling in Rabi-dimer model

The superradiant phase transition (SPT) controlled by the interacting strength between the two-level atom and the photons has been a hot topic in the Rabi model and the Rabi-dimer model. The latter describes two Rabi cavities coupled with an inter-cavity hopping parameter. Moreover, the SPT in the Rabi-dimer model is found to be the same universal class that in the Rabi model by investigating the correlation-length critical exponent. In this paper, we are concerned about whether the inter-cavity hopping parameter between two Rabi cavities (i.e., the Rabi-dimer model) will induce the SPT and to which the universal class of the phase transition belongs. We analytically derive the phase boundary of the SPT and investigate the ground-state properties of the system. We uncover that the inter-cavity induced SPT can be apparently understood from the ground-state energy and the ground-state photon population, as well as the ground-state expectation value of the squared anti-symmetric mode. From the scaling analysis of the fidelity susceptibility, we numerically verify that the SPT driven by the cavity coupling belongs to the same universal class as the one driven by the atom-cavity interaction. Our work enriches the studies on the SPT and its critical behaviors in the Rabi-dimer model.Comment: 11 pages, 6 figure

Infrared and Visible Image Fusion Based on Oversampled Graph Filter Banks

The infrared image (RI) and visible image (VI) fusion method merges complementary information from the infrared and visible imaging sensors to provide an effective way for understanding the scene. The graph filter bank-based graph wavelet transform possesses the advantages of the classic wavelet filter bank and graph representation of a signal. Therefore, we propose an RI and VI fusion method based on oversampled graph filter banks. Specifically, we consider the source images as signals on the regular graph and decompose them into the multiscale representations with M-channel oversampled graph filter banks. Then, the fusion rule for the low-frequency subband is constructed using the modified local coefficient of variation and the bilateral filter. The fusion maps of detail subbands are formed using the standard deviation-based local properties. Finally, the fusion image is obtained by applying the inverse transform on the fusion subband coefficients. The experimental results on benchmark images show the potential of the proposed method in the image fusion applications

A novel prestack sparse azimuthal AVO inversion

In this paper we demonstrate a new algorithm for sparse prestack azimuthal AVO inversion. A novel Euclidean prior model is developed to at once respect sparseness in the layered earth and smoothness in the model of reflectivity. Recognizing that methods of artificial intelligence and Bayesian computation are finding an every increasing role in augmenting the process of interpretation and analysis of geophysical data, we derive a generalized matrix-variate model of reflectivity in terms of orthogonal basis functions, subject to sparse constraints. This supports a direct application of machine learning methods, in a way that can be mapped back onto the physical principles known to govern reflection seismology. As a demonstration we present an application of these methods to the Marcellus shale. Attributes extracted using the azimuthal inversion are clustered using an unsupervised learning algorithm. Interpretation of the clusters is performed in the context of the Ruger model of azimuthal AVO

Degradable gene delivery systems based on Pluronics-modified low-molecular-weight polyethylenimine: preparation, characterization, intracellular trafficking, and cellular distribution

Wei Fan1,2,*, Xin Wu1,*, Baoyue Ding3,*, Jing Gao4, Zhen Cai1, Wei Zhang1, Dongfeng Yin1, Xiang Wang1, Quangang Zhu1, Jiyong Liu1, Xueying Ding4, Shen Gao1 1Department of Pharmaceutics, Changhai Hospital, Second Military Medical University, Shanghai, 2Department of Pharmaceutics, The 425th Hospital of PLA, Sanya, 3Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, 4Department of Pharmaceutics, School of Pharmacy, Second Military Medical University, Shanghai, People's Republic of China*These authors contributed equally to this workBackground: Cationic copolymers consisting of polycations linked to nonionic amphiphilic block polymers have been evaluated as nonviral gene delivery systems, and a large number of different polymers and copolymers of linear, branched, and dendrimeric architectures have been tested in terms of their suitability and efficacy for in vitro and in vivo transfection. However, the discovery of new potent materials still largely relies on empiric approaches rather than a rational design. The authors investigated the relationship between the polymers' structures and their biological performance, including DNA compaction, toxicity, transfection efficiency, and the effect of cellular uptake.Methods: This article reports the synthesis and characterization of a series of cationic copolymers obtained by grafting polyethyleneimine with nonionic amphiphilic surfactant polyether-Pluronic® consisting of hydrophilic ethylene oxide and hydrophobic propylene oxide blocks. Transgene expression, cytotoxicity, localization of plasmids, and cellular uptake of these copolymers were evaluated following in vitro transfection of HeLa cell lines with various individual components of the copolymers.Results: Pluronics can exhibit biological activity including effects on enhancing DNA cellular uptake, nuclear translocation, and gene expression. The Pluronics with a higher hydrophilic-lipophilic balance value lead to homogeneous distribution in the cytoplasm; those with a lower hydrophilic-lipophilic balance value prefer to localize in the nucleus.Conclusion: This Pluronic-polyethyleneimine system may be worth exploring as components in the cationic copolymers as the DNA or small interfering RNA/microRNA delivery system in the near future.Keywords: Pluronics, gene transfer, nonviral vectors, transfection efficiency, cellular uptak

Method of Reservoir Optimal Operation Based on Improved Simulated Annealing Genetic Algorithm

According to the specific circumstances of Wanjiazhai Reservoir, establish a reservoir optimal scheduling nonlinear mathematical model with a maximum generation capacity target, this paper uses an improved simulated annealing genetic algorithm to solve the model. The algorithm is in view of the defects of the traditional simulated annealing genetic algorithm to improve the algorithm from three aspects: introducing the niche technology, using adaptive crossover and mutation strategy, using the elitist strategy during the selection. Through examples are calculated and compared with the traditional simulated annealing genetic algorithm, the improved algorithm effectively overcomes the stagnation phenomenon, to enhance the global search ability. Its optimization performance is better than that of the traditional simulated annealing genetic algorithm

Identifying rheumatoid arthritis susceptibility genes using high-dimensional methods

Although several genes (including a strong effect in the human leukocyte antigen (HLA) region) and some environmental factors have been implicated to cause susceptibility to rheumatoid arthritis (RA), the etiology of the disease is not completely understood. The ability to screen the entire genome for association to complex diseases has great potential for identifying gene effects. However, the efficiency of gene detection in this situation may be improved by methods specifically designed for high-dimensional data. The aim of this study was to compare how three different statistical approaches, multifactor dimensionality reduction (MDR), random forests (RF), and an omnibus approach, worked in identifying gene effects (including gene-gene interaction) associated with RA. We developed a test set of genes based on previous linkage and association findings and tested all three methods. In the presence of the HLA shared-epitope factor, other genes showed weaker effects. All three methods detected SNPs in PTPN22 and TRAF1-C5 as being important. But we did not detect any new genes in this study. We conclude that the three high-dimensional methods are useful as an initial screening for gene associations to identify promising genes for further modeling and additional replication studies