Normal approximation and large deviations for the Robbins-Monro Process

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47650/1/440_2004_Article_BF00532261.pd

Parameters of the Magnetic Flux inside Coronal Holes

Parameters of magnetic flux distribution inside low-latitude coronal holes (CHs) were analyzed. A statistical study of 44 CHs based on Solar and Heliospheric Observatory (SOHO)/MDI full disk magnetograms and SOHO/EIT 284\AA images showed that the density of the net magnetic flux, $B_{{\rm net}}$, does not correlate with the associated solar wind speeds, $V_x$. Both the area and net flux of CHs correlate with the solar wind speed and the corresponding spatial Pearson correlation coefficients are 0.75 and 0.71, respectively. A possible explanation for the low correlation between $B_{{\rm net}}$ and $V_x$ is proposed. The observed non-correlation might be rooted in the structural complexity of the magnetic field. As a measure of complexity of the magnetic field, the filling factor, $f(r)$, was calculated as a function of spatial scales. In CHs, $f(r)$ was found to be nearly constant at scales above 2 Mm, which indicates a monofractal structural organization and smooth temporal evolution. The magnitude of the filling factor is 0.04 from the Hinode SOT/SP data and 0.07 from the MDI/HR data. The Hinode data show that at scales smaller than 2 Mm, the filling factor decreases rapidly, which means a mutlifractal structure and highly intermittent, burst-like energy release regime. The absence of necessary complexity in CH magnetic fields at scales above 2 Mm seems to be the most plausible reason why the net magnetic flux density does not seem to be related to the solar wind speed: the energy release dynamics, needed for solar wind acceleration, appears to occur at small scales below 1 Mm.Comment: 6 figures, approximately 23 pages. Accepted in Solar Physic

Evidence for gene-smoking interactions for hearing loss and deafness in Japanese American families

Background: This study investigated the relationship between smoking and hearing loss and deafness (HLD) and whether the relationship is modified by genetic variation. Data for these analyses was from the subset of Japanese American families collected as part of the American Diabetes Association Genetics of Non-insulin Dependent Diabetes Mellitus study. Logistic regression with generalized estimating equations assessed the relationship between HLD and smoking. Nonparametric linkage analysis identified genetic regions harboring HLD susceptibility genes and ordered subset analysis was used to identify regions showing evidence for gene-smoking interactions. Genetic variants within these candidate regions were then each tested for interaction with smoking using logistic regression models. Results: After adjusting for age, sex, diabetes status and smoking duration, for each pack of cigarettes smoked per day, risk of HLD increased 4.58 times (odds ratio (OR) = 4.58; 95% Confidence Interval (CI): (1.40,15.03)), and ever smokers were over 5 times more likely than nonsmokers to report HLD (OR = 5.22; 95% CI: (1.24, 22.03)). Suggestive evidence for linkage for HLD was observed in multiple genomic regions (Chromosomes 5p15, 8p23 and 17q21), and additional suggestive regions were identified when considering interactions with smoking status (Chromosomes 7p21, 11q23, 12q32, 15q26, and 20q13) and packs-per-day (Chromosome 8q21). Conclusions: To our knowledge this was the first report of possible gene-by-smoking interactions in HLD using family data. Additional work, including independent replication, is needed to understand the basis of these findings. HLD are important public health issues and understanding the contributions of genetic and environmental factors may inform public health messages and policies