Resolving The Moth at Millimeter Wavelengths

HD 61005, also known as "The Moth," is one of only a handful of debris disks that exhibit swept-back "wings" thought to be caused by interaction with the ambient interstellar medium (ISM). We present 1.3 mm Submillimeter Array (SMA) observations of the debris disk around HD 61005 at a spatial resolution of 1.9 arcsec that resolve the emission from large grains for the first time. The disk exhibits a double-peaked morphology at millimeter wavelengths, consistent with an optically thin ring viewed close to edge-on. To investigate the disk structure and the properties of the dust grains we simultaneously model the spatially resolved 1.3 mm visibilities and the unresolved spectral energy distribution. The temperatures indicated by the SED are consistent with expected temperatures for grains close to the blowout size located at radii commensurate with the millimeter and scattered light data. We also perform a visibility-domain analysis of the spatial distribution of millimeter-wavelength flux, incorporating constraints on the disk geometry from scattered light imaging, and find suggestive evidence of wavelength-dependent structure. The millimeter-wavelength emission apparently originates predominantly from the thin ring component rather than tracing the "wings" observed in scattered light. The implied segregation of large dust grains in the ring is consistent with an ISM-driven origin for the scattered light wings.Comment: 10 pages, 6 figure

Mortality Differences Between Traditional Medicare and Medicare Advantage: A Risk-Adjusted Assessment Using Claims Data.

Medicare Advantage (MA) has grown rapidly since the Affordable Care Act; nearly one-third of Medicare beneficiaries now choose MA. An assessment of the comparative value of the 2 options is confounded by an apparent selection bias favoring MA, as reflected in mortality differences. Previous assessments have been hampered by lack of access to claims diagnosis data for the MA population. An indirect comparison of mortality as an outcome variable was conducted by modeling mortality on a traditional fee-for-service (FFS) Medicare data set, applying the model to an MA data set, and then evaluating the ratio of actual-to-predicted mortality in the MA data set. The mortality model adjusted for clinical conditions and demographic factors. Model development considered the effect of potentially greater coding intensity in the MA population. Further analysis calculated ratios for subpopulations. Predicted, risk-adjusted mortality was lower in the MA population than in FFS Medicare. However, the ratio of actual-to-predicted mortality (0.80) suggested that the individuals in the MA data set were less likely to die than would be predicted had those individuals been enrolled in FFS Medicare. Differences between actual and predicted mortality were particularly pronounced in low income (dual eligibility), nonwhite race, high morbidity, and Health Maintenance Organization (HMO) subgroups. After controlling for baseline clinical risk as represented by claims diagnosis data, mortality differences favoring MA over FFS Medicare persisted, particularly in vulnerable subgroups and HMO plans. These findings suggest that differences in morbidity do not fully explain differences in mortality between the 2 programs

White matter changes and word finding failures with increasing age.

BACKGROUND: Increasing life expectancy necessitates the better understanding of the neurophysiological underpinnings of age-related cognitive changes. The majority of research examining structural-cognitive relationships in aging focuses on the role of age-related changes to grey matter integrity. In the current study, we examined the relationship between age-related changes in white matter and language production. More specifically, we concentrated on word-finding failures, which increase with age. METHODOLOGY/PRINCIPAL FINDINGS: We used Diffusion tensor MRI (a technique used to image, in vivo, the diffusion of water molecules in brain tissue) to relate white matter integrity to measures of successful and unsuccessful picture naming. Diffusion tensor images were used to calculate Fractional Anisotropy (FA) images. FA is considered to be a measure of white matter organization/integrity. FA images were related to measures of successful picture naming and to word finding failures using voxel-based linear regression analyses. Successful naming rates correlated positively with white matter integrity across a broad range of regions implicated in language production. However, word finding failure rates correlated negatively with a more restricted region in the posterior aspect of superior longitudinal fasciculus. CONCLUSIONS/SIGNIFICANCE: The use of DTI-MRI provides evidence for the relationship between age-related white matter changes in specific language regions and word finding failures in old age

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE

ALMA Observations of the Orion Proplyds

We present ALMA observations of protoplanetary disks ("proplyds") in the Orion Nebula Cluster. We imaged 5 individual fields at 856um containing 22 HST-identified proplyds and detected 21 of them. Eight of those disks were detected for the first time at submillimeter wavelengths, including the most prominent, well-known proplyd in the entire Orion Nebula, 114-426. Thermal dust emission in excess of any free-free component was measured in all but one of the detected disks, and ranged between 1-163 mJy, with resulting disk masses of 0.3-79 Mjup. An additional 26 stars with no prior evidence of associated disks in HST observations were also imaged within the 5 fields, but only 2 were detected. The disk mass upper limits for the undetected targets, which include OB stars, theta1Ori C and theta1Ori F, range from 0.1-0.6 Mjup. Combining these ALMA data with previous SMA observations, we find a lack of massive (>3 Mjup) disks in the extreme-UV dominated region of Orion, within 0.03 pc of O-star theta1Ori C. At larger separations from theta1Ori C, in the far-UV dominated region, there is a wide range of disk masses, similar to what is found in low-mass star forming regions. Taken together, these results suggest that a rapid dissipation of disk masses likely inhibits potential planet formation in the extreme-UV dominated regions of OB associations, but leaves disks in the far-UV dominated regions relatively unaffected.Comment: ApJ, in pres

Partial Dynamical Symmetry and Mixed Dynamics

Partial dynamical symmetry describes a situation in which some eigenstates have a symmetry which the quantum Hamiltonian does not share. This property is shown to have a classical analogue in which some tori in phase space are associated with a symmetry which the classical Hamiltonian does not share. A local analysis in the vicinity of these special tori reveals a neighbourhood of phase space foliated by tori. This clarifies the suppression of classical chaos associated with partial dynamical symmetry. The results are used to divide the states of a mixed system into ``chaotic'' and ``regular'' classes.Comment: 10 pages, Revtex, 3 figures, Phys. Rev. Lett. in pres

Psychosocial factors affecting variation in patient-reported outcomes after elbow fractures

Background. The purpose of this study was to identify factors associated with limitations in function measured by patient-reported outcome measures (PROMs) 6-9 months after elbow fractures in adults from a range of demographic, injury, psychological, and social variables measured within a week and 2-4 weeks after injury. Methods. We enrolled 191 adult patients sustaining an isolated elbow fracture and invited them to complete PROMs at their initial visit to the orthopedic outpatient clinic (within a maximum of 1 week after fracture), between 2 and 4 weeks, and between 6 and 9 months after injury; 183 patients completed the final assessment. Bivariate analysis was performed, followed by multivariable regression analysis accounting for multicollinearity. This was evaluated using partial R2, correlation matrices, and variable inflation factor assessment. Results. There was a correlation between multiple variables within a week of injury and 2-4 weeks after injury with PROMs 6-9 months after injury in bivariate analysis. Kinesiophobia measured within a week of injury and self-efficacy measured at 2-4 weeks were the strongest predictors of limitations 6-9 months after injury in multivariable regression. Regression models accounted for substantial variance in all PROMs at both time points. Conclusions. Developing effective coping strategies to overcome fears related to movement and reinjury and finding ways of persevering with activity despite pain within a month of injury may enhance recovery after elbow fractures. Heightened fears around movement and suboptimal coping ability are modifiable using evidence-based behavioral treatments

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository : structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample

Peer reviewe

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults.

In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood-oxygenation level-dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting-state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath-hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age-related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population-based Cambridge Centre for Ageing and Neuroscience cohort (Cam-CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task-based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task-based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical.The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) research was supported by the Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1). We are grateful to the Cam-CAN respondents and their primary care teams in Cambridge for their participation in this study. We also thank col- leagues at the MRC Cognition and Brain Sciences Unit MEG and MRI facilities for their assistance.This is the final version of the article. It first appeared at http://onlinelibrary.wiley.com/doi/10.1002/hbm.22768/ful