490 research outputs found
Exchange-correlation functionals from the strongly-interacting limit of DFT: Applications to model chemical systems
We study model one-dimensional chemical systems (representative of their
three-dimensional counterparts) using the strictly-correlated electrons (SCE)
functional, which, by construction, becomes asymptotically exact in the limit
of infinite coupling strength. The SCE functional has a highly non-local
dependence on the density and is able to capture strong correlation within
Kohn- Sham theory without introducing any symmetry breaking. Chemical systems,
however, are not close enough to the strong-interaction limit so that, while
ionization energies and the stretched H2 molecule are accurately described,
total energies are in general way too low. A correction based on the exact next
leading order in the expansion at infinite coupling strength of the
Hohenberg-Kohn functional largely improves the results.Comment: 9 pages, 6 figures. Submitted to PCCP's Themed Collection on Density
Functional Theory and its Application
Tracing the sites of obscured star formation in the Antennae galaxies with Herschel-PACS
FIR imaging of interacting galaxies allows locating even hidden sites of star
formation and measuring of the relative strength of nuclear and extra-nuclear
star formation. We want to resolve the star-forming sites in the nearby system
of the Antennae. Thanks to the unprecedented sharpness and depth of the PACS
camera onboard ESA's Herschel Space Observatory, it is possible for the first
time to achieve a complete assessment of individual star-forming knots in the
FIR with scan maps at 70, 100, and 160 um. We used clump extraction photometry
and SED diagnostics to derive the properties related to star-forming activity.
The PACS 70, 100, and 160 um maps trace the knotty structure of the most recent
star formation along an arc between the two nuclei in the overlap area. The
resolution of the starburst knots and additional multi-wavelength data allow
their individual star formation history and state to be analysed. In
particular, the brightest knot in the mid-infrared (K1), east of the southern
nucleus, exhibits the highest activity by far in terms of dust heating and star
formation rate, efficiency, and density. With only 2 kpc in diameter, this area
has a 10-1000 um luminosity, which is as high as that of our Milky Way. It
shows the highest deficiency in radio emission in the radio-to-FIR luminosity
ratio and a lack of X-ray emission, classifying it as a very young complex. The
brightest 100 and 160 um emission region (K2), which is close to the collision
front and consists of 3 knots, also shows a high star formation density and
efficiency and lack of X-ray emission in its most obscured part, but an excess
in the radio-to-FIR luminosity ratio. This suggests a young stage, too, but
different conditions in its interstellar medium. Our results provide important
checkpoints for numerical simulations of interacting galaxies when modelling
the star formation and stellar feedback.Comment: 4 pages, 4 figures, 2 tables (A&A Herschel special issue
The C-seal: A Biofragmentable Drain Protecting the Stapled Colorectal Anastomosis from Leakage
Colorectal anastomotic leakage (AL) is a serious complication in colorectal surgery leading to high morbidity and mortality rates1. The incidence of AL varies between 2.5 and 20% 2-5. Over the years, many strategies aimed at lowering the incidence of anastomotic leakage have been examined6, 7
Modeling Ketamine Effects on Synaptic Plasticity During the Mismatch Negativity
This paper presents a model-based investigation of mechanisms underlying the reduction of mismatch negativity (MMN) amplitudes under the NMDA-receptor antagonist ketamine. We applied dynamic causal modeling and Bayesian model selection to data from a recent ketamine study of the roving MMN paradigm, using a cross-over, double-blind, placebo-controlled design. Our modeling was guided by a predictive coding framework that unifies contemporary "adaptation” and "model adjustment” MMN theories. Comparing a series of dynamic causal models that allowed for different expressions of neuronal adaptation and synaptic plasticity, we obtained 3 major results: 1) We replicated previous results that both adaptation and short-term plasticity are necessary to explain MMN generation per se; 2) we found significant ketamine effects on synaptic plasticity, but not adaptation, and a selective ketamine effect on the forward connection from left primary auditory cortex to superior temporal gyrus; 3) this model-based estimate of ketamine effects on synaptic plasticity correlated significantly with ratings of ketamine-induced impairments in cognition and control. Our modeling approach thus suggests a concrete mechanism for ketamine effects on MMN that correlates with drug-induced psychopathology. More generally, this demonstrates the potential of modeling for inferring on synaptic physiology, and its pharmacological modulation, from electroencephalography dat
Health-Related Quality of Life, Treatment Satisfaction, and Costs Associated With Intraperitoneal Versus Subcutaneous Insulin Administration in Type 1 Diabetes: A randomized controlled trial
OBJECTIVE - To investigate the effects of continuous intraperitoneal insulin infusion (CIPII) compared with subcutaneous insulin on health-related quality of life (HRQOL) and treatment satisfaction, and to perform a cost analysis in type 1 diabetes. RESEARCH DESIGN AND METHODS - We used an open-label, prospective, crossover, randomized, 16-month study (N = 24). HRQOL and patient satisfaction were assessed with questionnaires (the 36-item short-form health survey [SF-36], the World Health Organization-Five Well-Being Index [WHO-5], and the Diabetes Treatment Satisfaction Questionnaire [DTSQ]). Direct costs of CIPII and continuous subcutaneous insulin infusion (CSII) were compared. RESULTS - Questionnaire scores were higher with CIPII than with subcutaneous therapy. Yearly direct pump- and procedure-associated costs for CIPII were estimated at 10,910 compared with 4,810 for CSII. C CONCLUSIONS - Apart from improving glycemic control, CIPII improved HRQOL and treatment satisfaction compared with subcutaneous insulin. Direct pump- and procedure-associated costs are considerably higher for CIPII, however
Evidence of negative energy balance using doubly labelled water in elite Kenyan endurance runners prior to competition
Previous studies have found Kenyan endurance runners to be in negative energy balance during training and prior to competition. The aim of the present study was to assess energy balance in nine elite Kenyan endurance runners during heavy training. Energy intake and expenditure were determined over 7d using weighed dietary intake and doubly labelled water, respectively. Athletes were on average in negative energy balance (mean energy intake 13 241 (SD 1330) kJ/d v. mean energy expenditure 14 611 (SD 1043) kJ/d; P=0·046), although there was no loss in body mass (mean 56·0 (SD 3·4) kg v. 55·7 (SD 3·6) kg; P=0·285). The calculation of underreporting was 13; (range −24 to +9%) and almost entirely accounted for by undereating (9% (range −55 to +39%)) as opposed to a lack of significant underrecording (i.e. total water intake was no different from water loss (mean 4·2 (SD 0·6) l/d v. 4·5 (SD 0·8) l/d; P=0·496)). Fluid intake was modest and consisted mainly of water (0·9 (SD 0·5) l/d) and milky tea (0·9 (SD 0·3) l/d). The diet was high in carbohydrate (67·3 (SD 7·8) %) and sufficient in protein (15·3 (SD 4·0) %) and fat (17·4 (SD 3·9) %). These results confirm previous observations that Kenyan runners are in negative energy balance during periods of intense training. A negative energy balance would result in a reduction in body mass, which, when combined with a high carbohydrate diet, would have the potential in the short term to enhance endurance running performance by reducing the energy cost of runnin
A Search for OH Megamasers at z > 0.1. III. The Complete Survey
We present the final results from the Arecibo Observatory OH megamaser
survey. We discuss in detail the properties of the remaining 18 OH megamasers
detected in the survey, including 3 redetections. We place upper limits on the
OH emission from 85 nondetections and examine the properties of 25 ambiguous
cases for which the presence or absence of OH emission could not be determined.
The complete survey has discovered 50 new OH megamasers (OHMs) in
(ultra)luminous infrared galaxies ([U]LIRGs) which doubles the sample of known
OHMs and increases the sample at z>0.1 sevenfold. The Arecibo OH megamaser
survey indicates that the OHM fraction in LIRGs is an increasing function of
the far-IR luminosity (L_{FIR}) and far-IR color, reaching a fraction of
roughly one third in the warmest ULIRGs. Significant relationships between OHMs
and their hosts are few, primarily due to a mismatch in size scales of measured
properties and an intrinsic scatter in OHM properties roughly equal to the span
of the dataset. We investigate relationships between OHMs and their hosts with
a variety of statistical tools including survival analysis, partial correlation
coefficients, and a principal component analysis. There is no apparent OH
megamaser ``fundamental plane.'' We compile data on all previously known OHMs
and evaluate the possible mechanisms and relationships responsible for OHM
production in merging systems. The OH-FIR relationship is reexamined using the
doubled OHM sample and found to be significantly flatter than previously
thought: L_{OH} ~ L_{FIR}^{1.2 +/- 0.1}. This near-linear dependence suggests a
mixture of saturated and unsaturated masers, either within individual galaxies
or across the sample.Comment: 28 pages, 14 figures, accepted by AJ. (AASTeX, includes emulateapj5
and onecolfloat5
Inferring on the intentions of others by hierarchical Bayesian learning
Inferring on others' (potentially time-varying) intentions is a fundamental problem during many social transactions. To investigate the underlying mechanisms, we applied computational modeling to behavioral data from an economic game in which 16 pairs of volunteers (randomly assigned to "player" or "adviser" roles) interacted. The player performed a probabilistic reinforcement learning task, receiving information about a binary lottery from a visual pie chart. The adviser, who received more predictive information, issued an additional recommendation. Critically, the game was structured such that the adviser's incentives to provide helpful or misleading information varied in time. Using a meta-Bayesian modeling framework, we found that the players' behavior was best explained by the deployment of hierarchical learning: they inferred upon the volatility of the advisers' intentions in order to optimize their predictions about the validity of their advice. Beyond learning, volatility estimates also affected the trial-by-trial variability of decisions: participants were more likely to rely on their estimates of advice accuracy for making choices when they believed that the adviser's intentions were presently stable. Finally, our model of the players' inference predicted the players' interpersonal reactivity index (IRI) scores, explicit ratings of the advisers' helpfulness and the advisers' self-reports on their chosen strategy. Overall, our results suggest that humans (i) employ hierarchical generative models to infer on the changing intentions of others, (ii) use volatility estimates to inform decision-making in social interactions, and (iii) integrate estimates of advice accuracy with non-social sources of information. The Bayesian framework presented here can quantify individual differences in these mechanisms from simple behavioral readouts and may prove useful in future clinical studies of maladaptive social cognition
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