204 research outputs found
Unusual Galactic Cosmic Ray Intensity and Spectral Changes Observed by V1 Near The Heliopause
Flux of Atmospheric Neutrinos
Atmospheric neutrinos produced by cosmic-ray interactions in the atmosphere
are of interest for several reasons. As a beam for studies of neutrino
oscillations they cover a range of parameter space hitherto unexplored by
accelerator neutrino beams. The atmospheric neutrinos also constitute an
important background and calibration beam for neutrino astronomy and for the
search for proton decay and other rare processes. Here we review the literature
on calculations of atmospheric neutrinos over the full range of energy, but
with particular attention to the aspects important for neutrino oscillations.
Our goal is to assess how well the properties of atmospheric neutrinos are
known at present.Comment: 68 pages, 26 figures. With permission from the Annual Review of
Nuclear & Particle Science. Final version of this material is scheduled to
appear in the Annual Review of Nuclear & Particle Science Vol. 52, to be
published in December 2002 by Annual Reviews (http://annualreviews.org
Very Cold Gas and Dark Matter
We have recently proposed a new candidate for baryonic dark matter: very cold
molecular gas, in near-isothermal equilibrium with the cosmic background
radiation at 2.73 K. The cold gas, of quasi-primordial abundances, is condensed
in a fractal structure, resembling the hierarchical structure of the detected
interstellar medium.
We present some perspectives of detecting this very cold gas, either directly
or indirectly. The H molecule has an "ultrafine" structure, due to the
interaction between the rotation-induced magnetic moment and the nuclear spins.
But the lines fall in the km domain, and are very weak. The best opportunity
might be the UV absorption of H in front of quasars. The unexpected cold
dust component, revealed by the COBE/FIRAS submillimetric results, could also
be due to this very cold H gas, through collision-induced radiation, or
solid H grains or snowflakes. The -ray distribution, much more
radially extended than the supernovae at the origin of cosmic rays
acceleration, also points towards and extended gas distribution.Comment: 16 pages, Latex pages, crckapb macro, 3 postscript figures, uuencoded
compressed tar file. To be published in the proceeedings of the
"Dust-Morphology" conference, Johannesburg, 22-26 January, 1996, D. Block
(ed.), (Kluwer Dordrecht
Nonthermal Emission from Star-Forming Galaxies
The detections of high-energy gamma-ray emission from the nearby starburst
galaxies M82 & NGC253, and other local group galaxies, broaden our knowledge of
star-driven nonthermal processes and phenomena in non-AGN star-forming
galaxies. We review basic aspects of the related processes and their modeling
in starburst galaxies. Since these processes involve both energetic electrons
and protons accelerated by SN shocks, their respective radiative yields can be
used to explore the SN-particle-radiation connection. Specifically, the
relation between SN activity, energetic particles, and their radiative yields,
is assessed through respective measures of the particle energy density in
several star-forming galaxies. The deduced energy densities range from O(0.1)
eV/cm^3 in very quiet environments to O(100) eV/cm^3 in regions with very high
star-formation rates.Comment: 17 pages, 5 figures, to be published in Astrophysics and Space
Science Proceeding
Diffuse Gamma Rays: Galactic and Extragalactic Diffuse Emission
"Diffuse" gamma rays consist of several components: truly diffuse emission
from the interstellar medium, the extragalactic background, whose origin is not
firmly established yet, and the contribution from unresolved and faint Galactic
point sources. One approach to unravel these components is to study the diffuse
emission from the interstellar medium, which traces the interactions of high
energy particles with interstellar gas and radiation fields. Because of its
origin such emission is potentially able to reveal much about the sources and
propagation of cosmic rays. The extragalactic background, if reliably
determined, can be used in cosmological and blazar studies. Studying the
derived "average" spectrum of faint Galactic sources may be able to give a clue
to the nature of the emitting objects.Comment: 32 pages, 28 figures, kapproc.cls. Chapter to the book "Cosmic
Gamma-Ray Sources," to be published by Kluwer ASSL Series, Edited by K. S.
Cheng and G. E. Romero. More details can be found at
http://www.gamma.mpe-garching.mpg.de/~aws/aws.htm
Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo
We use data from the second science run of the LIGO gravitational-wave
detectors to search for the gravitational waves from primordial black hole
(PBH) binary coalescence with component masses in the range 0.2--.
The analysis requires a signal to be found in the data from both LIGO
observatories, according to a set of coincidence criteria. No inspiral signals
were found. Assuming a spherical halo with core radius 5 kpc extending to 50
kpc containing non-spinning black holes with masses in the range 0.2--, we place an observational upper limit on the rate of PBH coalescence
of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.
Impacts of climate change on plant diseases – opinions and trends
There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods
Spike pattern recognition by supervised classification in low dimensional embedding space
© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio
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