686 research outputs found
gamma-ray DBSCAN: a clustering algorithm applied to Fermi-LAT gamma-ray data. I. Detection performances with real and simulated data
The Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a
topometric algorithm used to cluster spatial data that are affected by
background noise. For the first time, we propose the use of this method for the
detection of sources in gamma-ray astrophysical images obtained from the
Fermi-LAT data, where each point corresponds to the arrival direction of a
photon. We investigate the detection performance of the gamma-ray DBSCAN in
terms of detection efficiency and rejection of spurious clusters, using a
parametric approach, and exploring a large volume of the gamma-ray DBSCAN
parameter space. By means of simulated data we statistically characterize the
gamma-ray DBSCAN, finding signatures that differentiate purely random fields,
from fields with sources. We define a significance level for the detected
clusters, and we successfully test this significance with our simulated data.
We apply the method to real data, and we find an excellent agreement with the
results obtained with simulated data. We find that the gamma-ray DBSCAN can be
successfully used in the detection of clusters in gamma-ray data. The
significance returned by our algorithm is strongly correlated with that
provided by the Maximum Likelihood analysis with standard Fermi-LAT software,
and can be used to safely remove spurious clusters. The positional accuracy of
the reconstructed cluster centroid compares to that returned by standard
Maximum Likelihood analysis, allowing to look for astrophysical counterparts in
narrow regions, minimizing the chance probability in the counterpart
association. We find that gamma-ray DBSCAN is a powerful tool in the detection
of clusters in gamma-ray data, this method can be used both to look for
point-like sources, and extended sources, and can be potentially applied to any
astrophysical field related with detection of clusters in data.Comment: Accepted for publication in A&
Face yourself: The social neuroscience of mirror gazing
In philosophical and psychological accounts alike, it has been claimed that mirror gazing is like looking at ourselves as others. Social neuroscience and social psychology offer support for this view by showing that we use similar brain and cognitive mechanisms during perception of both others' and our own face. I analyse these premises to investigate the factors affecting the perception of one's own mirror image. I analyse mechanisms and processes involved in face perception, mimicry, and emotion recognition, and defend the following argument: because perception of others' face is affected by our feelings toward them, it is likely that feelings toward ourselves affect our responses to the mirror image. One implication is that negative self-feelings can affect mirror gazing instantiating a vicious cycle where the negative emotional response reflects a previously acquired attitude toward oneself. I conclude by discussing implications of this view for psychology and social studies
A novel mind-set in primate experimentation: Implications for primate welfare
Abstract We emphasize the importance of studying the primate brain in cognitive neuroscience and suggest a new mind-set in primate experimentation within the boundaries of animal welfare regulations. Specifically, we list the advantages of investigating both genes and neural mechanisms and processes in the emergence of behavioral and cognitive functions, and propose the establishment of an open field of primate research. The latter may be conducted by implementing and harmonizing experimental practices with ethical guidelines that regulate (1) management of natural parks with free-moving populations of target nonhuman primates, (2) establishment of indoor-outdoor labs for both system genetics and neuroscience investigations, and (3) hotel space and technologies which remotely collect and dislocate information regarding primates geographically located elsewhere.1 Introduction 2 Animal models in Neurobiology 3 The research domain criteria approach to Neuropsychiatry 4 The open niche of primate experimentation 4.1 Primate natural parks 4.2 Hotel space and remote technologies 5 Cost and benefits trade-offs of primate experimentation 6 Concluding remark
A new flaring high energy gamma-ray source
We report the detection of a new gamma-ray source in the Fermi-LAT sky using
a source detection tool based on the Minimal Spanning Tree algorithm. The
source, not reported in previous LAT catalogues but very recently observed in
the X-rays and optical bands, is characterized by an increasing gamma-ray
activity in 2012 June-September, reaching a weekly peak flux of
(3.3+-0.6)*10^-7 photons cm^-2 s^-1. A search for a possible counterpart
provides indication that it can be associated with the radio source NVSS
J141828+354250 whose optical SDSS colours are typical of a blazar.Comment: 4 pages, 3 figures. Accepted for publication in Astronomy &
Astrophysic
“Natural Laboratory Complex” for novel primate neuroscience
We propose novel strategies for primate experimentation that are ethically valuable and pragmatically useful for cognitive neuroscience and neuropsychiatric research. Specifically, we propose Natural Laboratory Complex or Natural Labs, which are a combination of indoor-outdoor structures for studying free moving and socially housed primates in natural or naturalistic environment. We contend that Natural Labs are pivotal to improve primate welfare, and at the same time to implement longitudinal and socio-ecological studies of primate brain and behavior. Currently emerging advanced technologies and social systems (including recent COVID-19 induced “remote” infrastructures) can speed-up cognitive neuroscience approaches in freely behaving animals. Experimental approaches in natural(istic) settings are not in competition with conventional approaches of laboratory investigations, and could establish several benefits at the ethical, experimental, and economic levels.Introduction Animal models in neuroscience - The rodent model - The non-human primate model - Optimizing cognitive neuroscience research with animal models Novel strategies for primate experimentation - Natural laboratory complex -- In situ Lab-in-Nature -- Ex situ Nature-in-Lab Harmonization of cost and benefit trade-offs - Ethical balance - Socioeconomic balance - Legal balance Conclusio
The Fermi blazars' divide based on the diagnostic of the SEDs peak frequencies
We have studied the quasi-simultaneous Spectral Energy Distributions (SED) of
48 LBAS blazars, detected within the three months of the LAT Bright AGN Sample
(LBAS) data taking period, combining Fermi and Swift data with radio
NIR-Optical and hard-X/gamma-ray data. Using these quasi-simultaneous SEDs,
sampling both the low and the high energy peak of the blazars broad band
emission, we were able to apply a diagnostic tool based on the estimate of the
peak frequencies of the synchrotron (S) and Inverse Compton (IC) components.
Our analysis shows a Fermi blazars' divide based on the peak frequencies of the
SED. The robust result is that the Synchrotron Self Compton (SSC) region
divides in two the plane were we plot the peak frequency of the synchrotron SED
vs the typical Lorentz factor of the electrons most contributing to the
synchrotron emission and to the inverse Compton process. Objects within or
below this region, radiating likely via the SSC process, are
high-frequency-peaked BL Lac object (HBL), or low/intermediate-frequency peaked
BL Lac object (LBL/IBL). All of the IBLs/LBLs within or below the SSC region
are not Compton dominated. The objects lying above the SSC region, radiating
likely via the External radiation Compton (ERC) process, are Flat Spectrum
Radio Quasars and IBLs/LBLs. All of the IBLs/LBLs in the ERC region show a
significant Compton dominance.Comment: Contribution to the Workshop SciNeGHe 2009/Gamma-ray Physics in the
LHC era (Assisi - Italy, Oct. 7-9 2009
ASTErIsM - Application of topometric clustering algorithms in automatic galaxy detection and classification
We present a study on galaxy detection and shape classification using
topometric clustering algorithms. We first use the DBSCAN algorithm to extract,
from CCD frames, groups of adjacent pixels with significant fluxes and we then
apply the DENCLUE algorithm to separate the contributions of overlapping
sources. The DENCLUE separation is based on the localization of pattern of
local maxima, through an iterative algorithm which associates each pixel to the
closest local maximum. Our main classification goal is to take apart elliptical
from spiral galaxies. We introduce new sets of features derived from the
computation of geometrical invariant moments of the pixel group shape and from
the statistics of the spatial distribution of the DENCLUE local maxima
patterns. Ellipticals are characterized by a single group of local maxima,
related to the galaxy core, while spiral galaxies have additional ones related
to segments of spiral arms. We use two different supervised ensemble
classification algorithms, Random Forest, and Gradient Boosting. Using a sample
of ~ 24000 galaxies taken from the Galaxy Zoo 2 main sample with spectroscopic
redshifts, and we test our classification against the Galaxy Zoo 2 catalog. We
find that features extracted from our pipeline give on average an accuracy of ~
93%, when testing on a test set with a size of 20% of our full data set, with
features deriving from the angular distribution of density attractor ranking at
the top of the discrimination power.Comment: 20 pages, 13 Figures, 8 Tables, Accepted for publication in the
Monthly Notices of the Royal Astronomical Societ
The 26 year-long X-ray light curve and the X-ray spectrum of the BL Lac Object 1E 1207.9+3945 in its brightest state
We studied the temporal and spectral evolution of the synchrotron emission
from the high energy peaked BL Lac object 1E 1207.9+3945. Two recent
observations have been performed by the XMM-Newton and Swift satellites; we
carried out X-ray spectral analysis for both of them, and photometry in
optical-ultraviolet filters for the Swift one. Combining the results thus
obtained with archival data we built the long-term X-ray light curve, spanning
a time interval of 26 years, and the Spectral Energy Distribution (SED) of this
source. The light curve shows a large flux increasing, about a factor of six,
in a time interval of a few years. After reaching its maximum in coincidence
with the XMM-Newton pointing in December 2000 the flux decreased in later
years, as revealed by Swift. The very good statistics available in the 0.5-10
keV XMM-Newton X-ray spectrum points out a highly significant deviation from a
single power law. A log-parabolic model with a best fit curvature parameter of
0.25 and a peak energy at ~1 keV describes well the spectral shape of the
synchrotron emission. The simultaneous fit of Swift UVOT and XRT data provides
a milder curvature (b~0.1) and a peak at higher energies (~15 keV), suggesting
a different state of source activity. In both cases UVOT data support the
scenario of a single synchrotron emission component extending from the
optical/UV to the X-ray band. New X-ray observations are important to monitor
the temporal and spectral evolution of the source; new generation gamma-ray
telescopes like AGILE and GLAST could for the first time detect its inverse
Compton emission.Comment: 7 pages, 6 figures, accepted for publication in A&
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