The predictability of stock market volatility in emerging economies: Relative roles of local,regional, and global business cycles

This paper explores the role of business cycle proxies, measured by the output gap at the global, regional, and local levels, as potential predictors of stock market volatility in the emerging BRICS nations. We observe that the emerging BRICS nations display a rather heterogeneous pattern when it comes to the relative role of idiosyncratic factors as a predictor of stock market volatility. While domestic output gap is found to capture significant predictive information for India and China particularly, the business cycles associated with emerging economies and the world in general are strongly important for the BRIC countries and weakly for South Africa, especially in the postglobal financial crisis era. The findings suggest that despite the increase in the financial integration of world capital markets, emerging economies can still bear significant exposures to idiosyncratic risk factors, an issue of high importance for the profitability of global diversification strategies.     

Enhanced performance of nano-sized SiC reinforced Al metal matrix nanocomposites synthesized through microwave sintering and hot extrusion techniques

In the present study, nano-sized SiC (0, 0.3, 0.5, 1.0 and 1.5 vol%) reinforced aluminum (Al) metal matrix composites were fabricated by microwave sintering and hot extrusion techniques. The structural (XRD, SEM), mechanical (nanoindentation, compression, tensile) and thermal properties (co-efficient of thermal expansion- CTE) of the developed Al-SiC nanocomposites were studied. The SEM/EDS mapping images show a homogeneous distribution of SiC nanoparticles into the Al matrix. A significant increase in the strength (compressive and tensile) of the Al-SiC nanocomposites with the addition of SiC content is observed. However, it is noticed that the ductility of Al-SiC nanocomposites decreases with increasing volume fraction of SiC. The thermal analysis indicates that CTE of Al-SiC nanocomposites decreases with the progressive addition of hard SiC nanoparticles. Overall, hot extruded Al 1.5 vol% SiC nanocomposites exhibited the best mechanical and thermal performance as compared to the other developed Al-SiC nanocomposites.     

Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR

In this paper, we first extract factors from a monthly dataset of 130 macroeconomic and financial variables. These extracted factors are then used to construct a factor‐augmented qualitative vector autoregressive (FA‐Qual VAR) model to forecast industrial production growth, inflation, the Federal funds rate, and the term spread based on a pseudo out‐of‐sample recursive forecasting exercise over an out‐of‐sample period of 1980:1 to 2014:12, using an in‐sample period of 1960:1 to 1979:12. Short‐, medium‐, and long‐run horizons of 1, 6, 12, and 24 months ahead are considered. The forecast from the FA‐Qual VAR is compared with that of a standard VAR model, a Qual VAR model, and a factor‐augmented VAR (FAVAR). In general, we observe that the FA‐Qual VAR tends to perform significantly better than the VAR, Qual VAR and FAVAR (barring some exceptions relative to the latter). In addition, we find that the Qual VARs are also well equipped in forecasting probability of recessions when compared to probit models.     

Mechanisms of cellular invasion by intracellular parasites

Numerous disease-causing parasites must invade host cells in order to prosper. Collectively, such pathogens are responsible for a staggering amount of human sickness and death throughout the world. Leishmaniasis, Chagas disease, toxoplasmosis, and malaria are neglected diseases and therefore are linked to socio-economical and geographical factors, affecting well-over half the world’s population. Such obligate intracellular parasites have co-evolved with humans to establish a complexity of specific molecular parasite–host cell interactions, forming the basis of the parasite’s cellular tropism. They make use of such interactions to invade host cells as a means to migrate through various tissues, to evade the host immune system, and to undergo intracellular replication. These cellular migration and invasion events are absolutely essential for the completion of the lifecycles of these parasites and lead to their for disease pathogenesis. This review is an overview of the molecular mechanisms of protozoan parasite invasion of host cells and discussion of therapeutic strategies, which could be developed by targeting these invasion pathways. Specifically, we focus on four species of protozoan parasites Leishmania, Trypanosoma cruzi, Plasmodium, and Toxoplasma, which are responsible for significant morbidity and mortality.     

CCDC103 mutations cause primary ciliary dyskinesia by disrupting assembly of ciliary dynein arms

Cilia are essential for fertilization, respiratory clearance, cerebrospinal fluid circulation and establishing laterality. Cilia motility defects cause primary ciliary dyskinesia (PCD, MIM244400), a disorder affecting 1:15,000-30,000 births. Cilia motility requires the assembly of multisubunit dynein arms that drive ciliary bending. Despite progress in understanding the genetic basis of PCD, mutations remain to be identified for several PCD-linked loci. Here we show that the zebrafish cilia paralysis mutant schmalhans (smh(tn222)) encodes the coiled-coil domain containing 103 protein (Ccdc103), a foxj1a-regulated gene product. Screening 146 unrelated PCD families identified individuals in six families with reduced outer dynein arms who carried mutations in CCDC103. Dynein arm assembly in smh mutant zebrafish was rescued by wild-type but not mutant human CCDC103. Chlamydomonas Ccdc103/Pr46b functions as a tightly bound, axoneme-associated protein. These results identify Ccdc103 as a dynein arm attachment factor that causes primary ciliary dyskinesia when mutated.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.     

ORGANIZATIONAL LEARNING AND VENDOR SUPPORT QUALITY BY THE USAGE OF APPLICATION SOFTWARE PACKAGES： A STUDY OF ASIAN ENTREPRENEURS

In this paper we study how organizational learning impacts organizational behavior, and howvendor support quality enhances product adoption and usage behavior.These constructs were verifiedusing Application Software Packages(ASP)-a prewritten, precoded, commercially available set ofprograms that eliminates the need for individuals or organizations to write their own softwareprograms for certain functions. The relationship between ASP usage, usage outcomes and useprocesses were also investigated. Two hundred and ninety-five Chinese, Indian, and Malayentrepreneurships were studied. It was found that usage outcome strongly determines usage, while useprocess has only an indirect relationship (via outcome) on usage. The impact of organizational learningand vendor service quality on usage, usage outcome, and use process were robust. Theoretical andpractical implications of the research are discussed.