333 research outputs found
Electronic structure, magnetism and superconductivity of MgCNi
The electronic structure of the newly discovered superconducting perovskite
MgCNi is calculated using the LMTO and KKR methods. The states near the
Fermi energy are found to be dominated by Ni-d. The Stoner factor is low while
the electron-phonon coupling constant is estimated to be about 0.7, which
suggests that the material is a conventional type of superconductor where T
is not affected by magnetic interactions. However, the proximity of the Fermi
energy to a large peak in the density of states in conjunction with the
reported non-stoichiometry of the compound, has consequences for the stability
of the results.Comment: 3 pages, 4 figure
Positive Imagery-Based Cognitive Bias Modification as a Web-Based Treatment Tool for Depressed Adults: A Randomized Controlled Trial.
Depression is a global health problem requiring treatment innovation. Targeting neglected cognitive aspects may provide a useful route. We tested a cognitive-training paradigm using positive mental imagery (imagery cognitive bias modification, imagery CBM), developed via experimental psychopathology studies, in a randomized controlled trial. Training was delivered via the Internet to 150 individuals with current major depression. Unexpectedly, there was no significant advantage for imagery CBM compared with a closely matched control for depression symptoms as a whole in the full sample. In exploratory analyses, compared with the control, imagery CBM significantly improved anhedonia over the intervention and improved depression symptoms as a whole for those participants with fewer than five episodes of depression and those who engaged to a threshold level of imagery. Results suggest avenues for improving imagery CBM to inform low-intensity treatment tools for depression. Anhedonia may be a useful treatment target for future work
Simultaneous removal of CO2, SO2, and NOx from flue gas by liquid phase dehumidification at cryogenic temperatures and low pressure
Published versio
Scaling of the distribution of fluctuations of financial market indices
We study the distribution of fluctuations over a time scale (i.e.,
the returns) of the S&P 500 index by analyzing three distinct databases.
Database (i) contains approximately 1 million records sampled at 1 min
intervals for the 13-year period 1984-1996, database (ii) contains 8686 daily
records for the 35-year period 1962-1996, and database (iii) contains 852
monthly records for the 71-year period 1926-1996. We compute the probability
distributions of returns over a time scale , where varies
approximately over a factor of 10^4 - from 1 min up to more than 1 month. We
find that the distributions for 4 days (1560 mins) are
consistent with a power-law asymptotic behavior, characterized by an exponent
, well outside the stable L\'evy regime . To
test the robustness of the S&P result, we perform a parallel analysis on two
other financial market indices. Database (iv) contains 3560 daily records of
the NIKKEI index for the 14-year period 1984-97, and database (v) contains 4649
daily records of the Hang-Seng index for the 18-year period 1980-97. We find
estimates of consistent with those describing the distribution of S&P
500 daily-returns. One possible reason for the scaling of these distributions
is the long persistence of the autocorrelation function of the volatility. For
time scales longer than days, our results are
consistent with slow convergence to Gaussian behavior.Comment: 12 pages in multicol LaTeX format with 27 postscript figures
(Submitted to PRE May 20, 1999). See
http://polymer.bu.edu/~amaral/Professional.html for more of our work on this
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