16,552 research outputs found
Radial Velocity Confirmation of a Binary Detected from Pulse Timings
A periodic variation in the pulse timings of the pulsating hot subdwarf B
star CS 1246 was recently discovered via the O-C diagram and suggests the
presence of a binary companion with an orbital period of two weeks. Fits to
this phase variation, when interpreted as orbital reflex motion, imply CS 1246
orbits a barycenter 11 light-seconds away with a velocity of 16.6 km/s. Using
the Goodman spectrograph on the SOAR telescope, we decided to confirm this
hypothesis by obtaining radial velocity measurements of the system over several
months. Our spectra reveal a velocity variation with amplitude, period, and
phase in accordance with the O-C diagram predictions. This corroboration
demonstrates that the rapid pulsations of hot subdwarf B stars can be adequate
clocks for the discovery of binary companions via the pulse timing method.Comment: Accepted for publication in ApJ Letters; 5 pages, 2 figures, 3
tables; uses emulateap
Experiential avoidance as a mechanism of change across cognitive-behavioral therapy in a sample of participants with heterogeneous anxiety disorders
Despite the substantial evidence that supports the efficacy of cognitive-behavioral therapy for the treatment of anxiety and related disorders, our understanding of mechanisms of change throughout treatment remains limited. The goal of the current study was to examine changes in experiential avoidance across treatment in a sample of participants (N = 179) with heterogeneous anxiety disorders receiving various cognitive-behavioral therapy protocols. Univariate latent growth curve models were conducted to examine change in experiential avoidance across treatment, followed by parallel process latent growth curve models to examine the relationship between change in experiential avoidance and change in anxiety symptoms. Finally, bivariate latent difference score models were conducted to examine the temporal precedence of change in experiential avoidance and change in anxiety. Results indicated that there were significant reductions in experiential avoidance across cognitive-behavioral treatment, and that change in experiential avoidance was significantly associated with change in anxiety. Results from the latent difference score models indicated that change in experiential avoidance preceded and predicted subsequent changes in anxiety, whereas change in anxiety did not precede and predict subsequent changes in experiential avoidance. Taken together, these results provide additional support for reductions in experiential avoidance as a transdiagnostic mechanism in cognitive-behavioral therapy.First author draf
Supporting a curriculum for delivering Type 2 diabetes patient self-management education: a patient-needs assessment
Distribution of Time-Averaged Observables for Weak Ergodicity Breaking
We find a general formula for the distribution of time-averaged observables
for systems modeled according to the sub-diffusive continuous time random walk.
For Gaussian random walks coupled to a thermal bath we recover ergodicity and
Boltzmann's statistics, while for the anomalous subdiffusive case a weakly
non-ergodic statistical mechanical framework is constructed, which is based on
L\'evy's generalized central limit theorem. As an example we calculate the
distribution of : the time average of the position of the particle,
for unbiased and uniformly biased particles, and show that exhibits
large fluctuations compared with the ensemble average .Comment: 5 pages, 2 figure
Expectancies, working alliance, and outcome in transdiagnostic and single diagnosis treatment for anxiety disorders: an investigation of mediation
Patients’ outcome expectancies and the working alliance are two psychotherapy process variables that researchers have found to be associated with treatment outcome, irrespective of treatment approach and problem area. Despite this, little is known about the mechanisms accounting for this association, and whether contextual factors (e.g., psychotherapy type) impact the strength of these relationships. The primary aim of this study was to examine whether patient-rated working alliance quality mediates the relationship between outcome expectancies and pre- to post-treatment change in anxiety symptoms using data from a recent randomized clinical trial comparing a transdiagnostic treatment (the Unified Protocol [UP]; Barlow et al., Unified protocol for transdiagnostic treatment of emotional disorders: Client workbook, Oxford University Press, New York, 2011a; Barlow et al., Unified protocol for transdiagnostic treatment of emotional disorders: Patient workbook. New York: Oxford University Press, 2017b) to single diagnosis protocols (SDPs) for patients with a principal heterogeneous anxiety disorder (n = 179). The second aim was to explore whether cognitive-behavioral treatment condition (UP vs. SDP) moderated this indirect relationship. Results from mediation and moderated mediation models indicated that, when collapsing across the two treatment conditions, the relationship between expectancies and outcome was partially mediated by the working alliance [B = 0.037, SE = 0.05, 95% CI (.005, 0.096)]. Interestingly, within-condition analyses showed that this conditional indirect effect was only present for SDP patients, whereas in the UP condition, working alliance did not account for the association between expectancies and outcome. These findings suggest that outcome expectancies and working alliance quality may interact to influence treatment outcomes, and that the nature and strength of the relationships among these constructs may differ as a function of the specific cognitive-behavioral treatment approach utilized.This study was funded by grant R01 MH090053 from the National Institutes of Health. (R01 MH090053 - National Institutes of Health)First author draf
Optimal Population Codes for Space: Grid Cells Outperform Place Cells
Rodents use two distinct neuronal coordinate systems to estimate their position: place fields in the hippocampus and grid fields in the entorhinal cortex. Whereas place cells spike at only one particular spatial location, grid cells fire at multiple sites that correspond to the points of an imaginary hexagonal lattice. We study how to best construct place and grid codes, taking the probabilistic nature of neural spiking into account. Which spatial encoding properties of individual neurons confer the highest resolution when decoding the animal’s position from the neuronal population response? A priori, estimating a spatial position from a grid code could be ambiguous, as regular periodic lattices possess translational symmetry. The solution to this problem requires lattices for grid cells with different spacings; the spatial resolution crucially depends on choosing the right ratios of these spacings across the population. We compute the expected error in estimating the position in both the asymptotic limit, using Fisher information, and for low spike counts, using maximum likelihood estimation. Achieving high spatial resolution and covering a large range of space in a grid code leads to a trade-off: the best grid code for spatial resolution is built of nested modules with different spatial periods, one inside the other, whereas maximizing the spatial range requires distinct spatial periods that are pairwisely incommensurate. Optimizing the spatial resolution predicts two grid cell properties that have been experimentally observed. First, short lattice spacings should outnumber long lattice spacings. Second, the grid code should be self-similar across different lattice spacings, so that the grid field always covers a fixed fraction of the lattice period. If these conditions are satisfied and the spatial “tuning curves” for each neuron span the same range of firing rates, then the resolution of the grid code easily exceeds that of the best possible place code with the same number of neurons
Communications Biophysics
Contains reports on two research projects.United States Air Force (Contract AF19(604)-4112)United States National Institute of Neurological Diseases and Blindness, U.S. Public Health Service (BT-437)United States National Institute of Neurological Diseases and Blindness (B 369 Physiology)United States Navy, Office of Naval Research, (NR 101-445))United States Air Force, Office of Scientific Research (AF-49-(638)-98)
Examining hope as a transdiagnostic mechanism of change across anxiety disorders and CBT treatment protocols.
Hope is a trait that represents the capacity to identify strategies or pathways to achieve goals and the motivation or agency to effectively pursue those pathways. Hope has been demonstrated to be a robust source of resilience to anxiety and stress and there is limited evidence that, as has been suggested for decades, hope may function as a core process or transdiagnostic mechanism of change in psychotherapy. The current study examined the role of hope in predicting recovery in a clinical trial in which 223 individuals with 1 of 4 anxiety disorders were randomized to transdiagnostic cognitive behavior therapy (CBT), disorder-specific CBT, or a waitlist controlled condition. Effect size results indicated moderate to large intraindividual increases in hope, that changes in hope were consistent across the five CBT treatment protocols, that changes in hope were significantly greater in CBT relative to waitlist, and that changes in hope began early in treatment. Results of growth curve analyses indicated that CBT was a robust predictor of trajectories of change in hope compared to waitlist, and that changes in hope predicted changes in both self-reported and clinician-rated anxiety. Finally, a statistically significant indirect effect was found indicating that the effects of treatment on changes in anxiety were mediated by treatment effects on hope. Together, these results suggest that hope may be a promising transdiagnostic mechanism of change that is relevant across anxiety disorders and treatment protocols.R01 MH090053 - NIMH NIH HHSAccepted manuscrip
Hubble Space Telescope Images of Magellanic Cloud Planetary Nebulae: Data and Correlations across Morphological Classes
The morphology of planetary nebulae (PNe) provides an essential tool for
understanding their origin and evolution, as it reflects both the dynamics of
the gas ejected during the TP-AGB phase, and the central star energetics. Here
we study the morphology of 27 Magellanic Cloud planetary nebulae (MCPNe) and
present an analysis of their physical characteristics across morphological
classes. Similar studies have been successfully carried out for galactic PNe,
but were compromised by the uncertainty of individual PN distances. We present
our own HST/FOC images of 15 Magellanic Cloud PNe (MCPNe) acquired through a
narrow-band lambda 5007 [O III] filter. We use the Richardson-Lucy
deconvolution technique on these pre-COSTAR images to achieve post-COSTAR
quality. Three PNe imaged before and after COSTAR confirm the high reliability
of our deconvolution procedure. We derive morphological classes, dimensions,
and surface photometry for all these PNe. We have combined this sample with
HST/PC1 images of 15 MCPNe, three of which are in common with the FOC set,
acquired by Dopita et al. (1996), to obtain the largest MCPN sample ever
examined from the morphological viewpoint. By using the whole database,
supplemented with published data from the literature, we have analyzed the
properties of the MCPNe and compared them to a typical, complete galactic
sample. Morphology of the MCPNe is then correlated with PN density, chemistry,
and evolution.Comment: text file lstanghe_mcpn.tex (LaTex); Figures 2 through 10, Figure 5
is in 3 parts (a,b,c); Figure 1 available by regular mail only; ApJ, in
press, November 10, 199
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