Abrupt longitudinal magnetic field changes in flaring active regions

We characterize the changes in the longitudinal photospheric magnetic field during 38 X-class and 39 M-class flares within $65^{\circ}$ of disk-center using 1-minute GONG magnetograms. In all 77 cases we identify at least one site in the flaring active region where clear, permanent, stepwise field changes occurred. The median duration of the field changes was about 15 minutes and was approximately equal for X-class and for M-class flares. The absolute values of the field changes ranged from the detection limit of $\sim\!\!10$~G to as high as $\sim\!\!450$~G in two exceptional cases. The median value was 69~G. Field changes were significantly stronger for X-class than for M-class flares and for limb flares than for disk-center flares. Longitudinal field changes less than 100~G tended to decrease longitudinal field strengths, both close to disk-center and close to the limb, while field changes greater than 100~G showed no such pattern. Likewise, longitudinal flux strengths tended to decrease during flares. Flux changes, particularly net flux changes near disk-center, correlated better than local field changes with GOES peak X-ray flux. The strongest longitudinal field and flux changes occurred in flares observed close to the limb. We estimate the change of Lorentz force associated with each flare and find that this is large enough in some cases to power seismic waves. We find that longitudinal field decreases would likely outnumber increases at all parts of the solar disk within $65^{\circ}$ of disk-center, as in our observations, if photospheric field tilts increase during flares as predicted by Hudson et al.Comment: Accepted to Ap

Structure and correlates of cognitive aging in a narrow age cohort

Aging-related changes occur for multiple domains of cognitive functioning. An accumulating body of research indicates that, rather than representing statistically independent phenomena, aging-related cognitive changes are moderately to strongly correlated across domains. However, previous studies have typically been conducted in age-heterogeneous samples over longitudinal time lags of 6 or more years, and have failed to consider whether results are robust to a comprehensive set of controls. Capitalizing on 3-year longitudinal data from the Lothian Birth Cohort of 1936, we took a longitudinal narrow age cohort approach to examine cross-domain cognitive change interrelations from ages 70 to 73 years. We fit multivariate latent difference score models to factors representing visuospatial ability, processing speed, memory, and crystallized ability. Changes were moderately interrelated, with a general factor of change accounting for 47% of the variance in changes across domains. Change interrelations persisted at close to full strength after controlling for a comprehensive set of demographic, physical, and medical factors including educational attainment, childhood intelligence, physical function, APOE genotype, smoking status, diagnosis of hypertension, diagnosis of cardiovascular disease, and diagnosis of diabetes. Thus, the positive manifold of aging-related cognitive changes is highly robust in that it can be detected in a narrow age cohort followed over a relatively brief longitudinal period, and persists even after controlling for many potential confounders

Abrupt Longitudinal Magnetic Field Changes and Ultraviolet Emissions Accompanying Solar Flares

We have used Transition Region and Coronal Explorer (TRACE) 1600 \AA images and Global Oscillation Network Group (GONG) magnetograms to compare ultraviolet (UV) emissions from the chromosphere to longitudinal magnetic field changes in the photosphere during four X-class solar flares. An abrupt, significant, and persistent change in the magnetic field occurred across more than ten pixels in the GONG magnetograms for each flare. These magnetic changes lagged the GOES flare start times in all cases, showing that they were consequences and not causes of the flares. Ultraviolet emissions were spatially coincident with the field changes. The UV emissions tended to lag the GOES start times for the flares, and led the changes in the magnetic field in all pixels except one. The UV emissions led the photospheric field changes by 4 minutes on average with the longest lead being 9 minutes, however, the UV emissions continued for tens of minutes, and more than an hour in some cases, after the field changes were complete. The observations are consistent with the picture in which an Alfv\'{e}n wave from the field reconnection site in the corona propagates field changes outward in all directions near the onset of the impulsive phase, including downwards through the chromosphere and into the photosphere, causing the photospheric field changes, whereas the chromosphere emits in the UV in the form of flare kernels, ribbons and sequential chromospheric brightenings during all phases of the flare

Alzheimer's Disease Prediction Using Longitudinal and Heterogeneous Magnetic Resonance Imaging

Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer's disease (AD) prediction and diagnosis. While traditional MRI-based diagnosis uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main difficulties arise in longitudinal MRI-based diagnosis: (1) the inconsistent longitudinal scans among subjects (i.e., different scanning time and different total number of scans); (2) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a novel feature selection and estimation method which can be applied to extract features from the heterogeneous longitudinal MRI. A key ingredient of our method is the combination of smoothing splines and the $l_1$-penalty. We perform experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results corroborate the advantages of the proposed method for AD prediction in longitudinal studies

Longitudinal RNA-Seq analysis of acute and chronic neurogenic skeletal muscle atrophy.

Skeletal muscle is a highly adaptable tissue capable of changes in size, contractility, and metabolism according to functional demands. Atrophy is a decline in mass and strength caused by pathologic loss of myofibrillar proteins, and can result from disuse, aging, or denervation caused by injury or peripheral nerve disorders. We provide a high-quality longitudinal RNA-Seq dataset of skeletal muscle from a cohort of adult C57BL/6J male mice subjected to tibial nerve denervation for 0 (baseline), 1, 3, 7, 14, 30, or 90 days. Using an unbiased genomics approach to identify gene expression changes across the entire longitudinal course of muscle atrophy affords the opportunity to (1) establish acute responses to denervation, (2) detect pathways that mediate rapid loss of muscle mass within the first week after denervation, and (3) capture the molecular phenotype of chronically atrophied muscle at a stage when it is largely resistant to recovery