The total cost of misclassification in credit scoring: A comparison of generalized linear models and generalized additive models

This study examines whether the evaluation of a bankruptcy prediction model should take into account the total cost of misclassification. For this purpose, we introduce and apply a validity measure in credit scoring that is based on the total cost of misclassification. Specifically, we use comprehensive data from the annual financial statements of a sample of German companies and analyze the total cost of misclassification by comparing a generalized linear model and a generalized additive model with regard to their ability to predict a company's probability of default. On the basis of these data, the validity measure we introduce shows that, compared to generalized linear models, generalized additive models can reduce substantially the extent of misclassification and the total cost that this entails. The validity measure we introduce is informative and justifies the argument that generalized additive models should be preferred, although such models are more complex than generalized linear models. We conclude that to balance a model's validity and complexity, it is necessary to take into account the total cost of misclassification.     

Re-evaluation of protein kinase CK2 pleiotropy: new insights provided by a phosphoproteomics analysis of CK2 knockout cells

CK2 denotes a ubiquitous and pleiotropic protein kinase whose holoenzyme is composed of two catalytic (α and/or α′) and two regulatory β subunits. The CK2 consensus sequence, S/T-x-x-D/E/pS/pT is present in numerous phosphosites, but it is not clear how many of these are really generated by CK2. To gain information about this issue, advantage has been taken of C2C12 cells entirely deprived of both CK2 catalytic subunits by the CRISPR/Cas9 methodology. A comparative SILAC phosphoproteomics analysis reveals that, although about 30% of the quantified phosphosites do conform to the CK2 consensus, only one-third of these are substantially reduced in the CK2α/α′^(?/?) cells, consistent with their generation by CK2. A parallel study with C2C12 cells deprived of the regulatory β subunit discloses a role of this subunit in determining CK2 targeting. We also find that phosphosites notoriously generated by CK2 are not fully abrogated in CK2α/α′^(?/?) cells, while some phosphosites unrelated to CK2 are significantly altered. Collectively taken our data allow to conclude that the phosphoproteome generated by CK2 is not as ample and rigidly pre-determined as it was believed before. They also show that the lack of CK2 promotes phosphoproteomics perturbations attributable to kinases other than CK2.     

ePTFE人工血管管壁结构及其体外性能的试验研究

对国内外两组膨体聚四氟乙烯(ePTFE)人工血管从管壁结构、理化性能和生物力学性能进行对比研究.通过试验研究两组人造血管管壁的宏观及微观结构、表面润湿性、结晶度和融熔温度、周/轴向拉伸、顶破拉伸以及手术线固位强力,对比两组样品的性能差异,并分析了导致差异的可能原因,讨论了管壁结构、理化性能与力学特性之间的关系.研究结果表明,国产和进口ePTFE人工血管试样均为双层结构,两者都有良好的疏水性表面和抗水渗透性.但进口试样具有更加规整均匀的节点和纤维形态结构,有利于人工血管的生物耐久性.     

The Role of Survey Data in Nowcasting Euro Area GDP Growth

This paper evaluates the impact of new releases of financial, real activity and survey data on nowcasting euro area gross domestic product (GDP). We show that all three data categories positively impact on the accuracy of GDP nowcasts, whereby the effect is largest in the case of real activity data. When treating variables as if they were all published at the same time and without any time lag, financial series lose all their significance, while survey data remain an important ingredient for the nowcasting exercise. The subsequent analysis shows that the sectoral coverage of survey data, which is broader than that of timely available real activity data, as well as their information content stemming from questions focusing on agents' expectations, are the main sources of the ‘genuine’ predictive power of survey data. When the forecast period is restricted to the 2008–09 financial crisis, the main change is an enhanced forecasting role for financial data. Copyright © 2015 John Wiley & Sons, Ltd.     

Forecasting Government Bond Yields with Neural Networks Considering Cointegration

This paper discusses techniques that might be helpful in predicting interest rates and tries to evaluate a new hybrid forecasting approach. Results of examining government bond yields in Germany and France reported in this study indicate that a hybrid forecasting approach which combines techniques of cointegration analysis with neural network (NN) forecasting models can produce superior results to the use of NN forecasting models alone. The findings documented in this paper could be a consequence of the fact that examining differenced data under certain conditions will lead to a loss of information and that the inclusion of the error correction term from the cointegration model can help to cope with this problem. The paper also discusses some possibly interesting directions for further research. Copyright © 2015 John Wiley & Sons, Ltd.     

Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.