Modification of electronic structure, magnetic structure, and topological phase of bismuthene by point defects

This paper reveals how the electronic structure, magnetic structure, and topological phase of two-dimensional (2D), single-layer structures of bismuth are modified by point defects. We first showed that a free-standing, single-layer, hexagonal structure of bismuth, named h-bismuthene, exhibits nontrivial band topology. We then investigated interactions between single foreign adatoms and bismuthene structures, which comprise stability, bonding, electronic structure, and magnetic structures. Localized states in diverse locations of the band gap and resonant states in band continua of bismuthene are induced upon the adsorption of different adatoms, which modify electronic and magnetic properties. Specific adatoms result in reconstruction around the adsorption site. Single vacancies and divacancies can form readily in bismuthene structures and remain stable at high temperatures. Through rebondings, Stone-Whales-type defects are constructed by divacancies, which transform into a large hole at high temperature. Like adsorbed adatoms, vacancies induce also localized gap states, which can be eliminated through rebondings in divacancies. We also showed that not only the optical and magnetic properties, but also the topological features of pristine h-bismuthene can be modified by point defects. The modification of the topological features depends on the energies of localized states and also on the strength of coupling between point defects. © 2017 American Physical Society

Using PCA-based neural network committee model for early warning of bank failure

2nd International Conference on Natural Computation, ICNC 2006 --24 September 2006 through 28 September 2006 -- Xi'an --As the Basel-II Accord is deemed to be an international standard to require essential capital ratios for all commercial banks, early warning of bank failure becomes critical more than ever. In this study, we propose the use of combining multiple neural network models based on transformed input variables to predict bank failure in the early stage. Experimental results show that: 1) PCA-based feature transformation technique effectively promotes an early warning capability of neural network models by reducing type-I error rate; and 2) the committee of multiple neural networks can significantly improve the predictability of a single neural network model when PCA-based transformed features are employed, especially in the long-term forecasting by showing comparable predictability of raw features models in short-term period. © Springer-Verlag Berlin Heidelberg 2006

Ensemble prediction of commercial bank failure through diversification of input features

19th Australian Joint Conference onArtificial Intelligence, AI 2006 --4 December 2006 through 8 December 2006 -- Hobart, TAS --As primary focus of banking regulation and supervision is being shifted toward internal risk management for all commercial banks, financial data mining task such as an early warning of bank failure becomes more critical than ever. In this study, we examine the effect of variable selection methods for intelligent bankruptcy prediction models. Moreover, an augmented stacked generalizer that utilizes diversified feature subsets during its learning phase is suggested as an effective ensemble method for promoting independencies among base prediction models. Empirical results show that the augmented stacked generalizer significantly improves overall predictability by reducing the more costly type-I error rate compared against both popular bagging and standard stacking procedures. © Springer-Verlag Berlin Heidelberg 2006

Prediction of commercial bank failure via multivariate statistical analysis of financial structures: The Turkish case

The objective of this paper is to propose a methodological framework for constructing the integrated early warning system (IEWS) that can be used as a decision support tool in bank examination and supervision process for detection of banks, which are experiencing serious problems. Sample and variable set of the study contains 40 privately owned Turkish commercial banks (21 banks failed during the period 1997-2003) and their financial ratios. Well known multivariate statistical technique (principal component analysis), was used to explore the basic financial characteristics of the banks, and discriminant, logit and probit models were estimated based on these characteristics to construct IEWS. Also, importance of early warning systems in bank examination was evaluated with respect to cost of failure. Results of the study show that, if IEWS was effectively employed in bank supervision, it can be possible to avoid from the bank restructuring costs at a significant amount of rate in the long run. © 2004 Elsevier B.V. All rights reserved

Performances of Inflammatory Back Pain Criteria in Axial Psoriatic Arthritis

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Serum irisin levels in colorectal cancer patients

OBJECTIVE: There are limited studies investigating the role of irisin in colorectal cancer, and the results are diverse. The role of irisin in colorectal cancer patients was investigated in this study. PATIENTS AND METHODS: This cross-sectional study included 53 patients diagnosed with colorectal cancer (CRC) and 87 healthy volunteers. Serum irisin, glucose, insulin, C-peptide, and whole blood hemoglobin A1c (HbA1c) levels were measured in venous blood samples taken from patients and the control group. RESULTS: The mean serum irisin levels were significantly lower in the patient group (23.97 ± 16.94 ng/mL) than in the control group (32.71 ± 17.26 ng/mL) (p = 0.004). Serum glucose levels were 96.58 ± 15.12 mg/dL in the patient group and 81.91 ± 11.24 mg/dL in the control group. Serum glucose levels were significantly higher in the patient group than in the control group (p < 0.01). In the patient group, there was no statistically significant difference between metastasis (+) patients and metastasis (-) patients in terms of serum irisin levels (27.53 ± 18.48 ng/mL and 21.23 ± 15.43 ng/mL, respectively; p = 0.182). CONCLUSIONS: Our study has provided new insights into the potential role of irisin in CRC. However, further studies, including in vitro, in vivo, and larger patient groups, are necessary to fully understand the potential of irisin as a biomarker or therapeutic target for CRC and other diseases

Characteristics predicting tuberculosis risk under tumor necrosis factor-? inhibitors: Report from a large multicenter cohort with high background prevalence

PubMed ID: 26773107Objective. Screening strategies for latent tuberculosis (TB) before starting tumor necrosis factor (TNF)- inhibitors have decreased the prevalence of TB among patients who are treated with these agents. However, despite vigilant screening, TB continues to be an important problem, especially in parts of the world with a high background TB prevalence. The aim of this study was to determine the factors related to TB among a large multicenter cohort of patients who were treated with anti-TNF. Methods. Fifteen rheumatology centers participated in this study. Among the 10,434 patients who were treated with anti-TNF between September 2002 and September 2012, 73 (0.69%) had developed TB. We described the demographic features and disease characteristics of these 73 patients and compared them to 7695 patients who were treated with anti-TNF, did not develop TB, and had complete data available. Results. Among the 73 patients diagnosed with TB (39 men, 34 women, mean age 43.6 ± 13 yrs), the most frequent diagnoses were ankylosing spondylitis (n = 38) and rheumatoid arthritis (n = 25). More than half of the patients had extrapulmonary TB (39/73, 53%). Six patients died (8.2%). In the logistic regression model, types of anti-TNF drugs [infliximab (IFX), OR 3.4, 95% CI 1.88-6.10, p = 0.001] and insufficient and irregular isoniazid use (< 9 mos; OR 3.15, 95% CI 1.43-6.9, p = 0.004) were independent predictors of TB development. Conclusion. Our results suggest that TB is an important complication of anti-TNF therapies in Turkey. TB chemoprophylaxis less than 9 months and the use of IFX therapy were independent risk factors for TB development. Copyright © 2016 The Journal of Rheumatology. All rights reserved

Characteristics predicting tuberculosis risk under tumor necrosis factor-α inhibitors: Report from a large multicenter cohort with high background prevalence

Objective. Screening strategies for latent tuberculosis (TB) before starting tumor necrosis factor (TNF)- inhibitors have decreased the prevalence of TB among patients who are treated with these agents. However, despite vigilant screening, TB continues to be an important problem, especially in parts of the world with a high background TB prevalence. The aim of this study was to determine the factors related to TB among a large multicenter cohort of patients who were treated with anti-TNF. Methods. Fifteen rheumatology centers participated in this study. Among the 10,434 patients who were treated with anti-TNF between September 2002 and September 2012, 73 (0.69%) had developed TB. We described the demographic features and disease characteristics of these 73 patients and compared them to 7695 patients who were treated with anti-TNF, did not develop TB, and had complete data available. Results. Among the 73 patients diagnosed with TB (39 men, 34 women, mean age 43.6 ± 13 yrs), the most frequent diagnoses were ankylosing spondylitis (n = 38) and rheumatoid arthritis (n = 25). More than half of the patients had extrapulmonary TB (39/73, 53%). Six patients died (8.2%). In the logistic regression model, types of anti-TNF drugs [infliximab (IFX), OR 3.4, 95% CI 1.88-6.10, p = 0.001] and insufficient and irregular isoniazid use (< 9 mos; OR 3.15, 95% CI 1.43-6.9, p = 0.004) were independent predictors of TB development. Conclusion. Our results suggest that TB is an important complication of anti-TNF therapies in Turkey. TB chemoprophylaxis less than 9 months and the use of IFX therapy were independent risk factors for TB development. Copyright © 2016 The Journal of Rheumatology. All rights reserved