997 research outputs found
Extragalactic jets on subpc and large scales
Jets can be probed in their innermost regions (d~0.1 pc) through the study of
the relativistically-boosted emission of blazars. On the other extreme of
spatial scales, the study of structure and dynamics of extragalactic
relativistic jets received renewed impulse after the discovery, made by
Chandra, of bright X-ray emission from regions at distances larger than
hundreds of kpc from the central engine. At both scales it is thus possible to
infer some of the basic parameters of the flow (speed, density, magnetic field
intensity, power). After a brief review of the available observational
evidence, I discuss how the comparison between the physical quantities
independently derived at the two scales can be used to shed light on the global
dynamics of the jet, from the innermost regions to the hundreds of kpc scale.Comment: Proceedings of the 5th Stromlo Symposium: Disks, Winds, and Jets -
from Planets to Quasars. Accepted, to be published in Astrophysics & Space
Scienc
Valiant's model: from exponential sums to exponential products
12 pagesWe study the power of big products for computing multivariate polynomials in a Valiant-like framework. More precisely, we define a new class \vpip as the set of families of polynomials that are exponential products of easily computable polynomials. We investigate the consequences of the hypothesis that these big products are themselves easily computable. For instance, this hypothesis would imply that the nonuniform versions of P and NP coincide. Our main result relates this hypothesis to Blum, Shub and Smale's algebraic version of P versus NP. Let be a field of characteristic 0. Roughly speaking, we show that in order to separate \p_K from \np_K using a problem from a fairly large class of ``simple'' problems, one should first be able to show that exponential products are not easily computable. The class of ``simple'' problems under consideration is the class of NP problems in the structure , in which multiplication is not allowed
Optical investigation of the charge-density-wave phase transitions in
We have measured the optical reflectivity of the quasi
one-dimensional conductor from the far infrared up to the
ultraviolet between 10 and 300 using light polarized along and normal to
the chain axis. We find a depletion of the optical conductivity with decreasing
temperature for both polarizations in the mid to far-infrared region. This
leads to a redistribution of spectral weight from low to high energies due to
partial gapping of the Fermi surface below the charge-density-wave transitions
at 145 K and 59 K. We deduce the bulk magnitudes of the CDW gaps and discuss
the scattering of ungapped free charge carriers and the role of fluctuations
effects
Dynamical aspects of quantum entanglement for weakly coupled kicked tops
We investigate how the dynamical production of quantum entanglement for
weakly coupled, composite quantum systems is influenced by the chaotic dynamics
of the corresponding classical system, using coupled kicked tops. The linear
entropy for the subsystem (a kicked top) is employed as a measure of
entanglement. A perturbative formula for the entanglement production rate is
derived. The formula contains a correlation function that can be evaluated only
from the information of uncoupled tops. Using this expression and the
assumption that the correlation function decays exponentially which is
plausible for chaotic tops, it is shown that {\it the increment of the strength
of chaos does not enhance the production rate of entanglement} when the
coupling is weak enough and the subsystems (kicked tops) are strongly chaotic.
The result is confirmed by numerical experiments. The perturbative approach is
also applied to a weakly chaotic region, where tori and chaotic sea coexist in
the corresponding classical phase space, to reexamine a recent numerical study
that suggests an intimate relationship between the linear stability of the
corresponding classical trajectory and the entanglement production rate.Comment: 16 pages, 11 figures, submitted to Phys. Rev.
Epidemics in Adaptive Social Networks with Temporary Link Deactivation
Disease spread in a society depends on the topology of the network of social contacts. Moreover, individuals may respond to the epidemic by adapting their contacts to reduce the risk of infection, thus changing the network structure and affecting future disease spread. We propose an adaptation mechanism where healthy individuals may choose to temporarily deactivate their contacts with sick individuals, allowing reactivation once both individuals are healthy. We develop a mean-field description of this system and find two distinct regimes: slow network dynamics, where the adaptation mechanism simply reduces the effective number of contacts per individual, and fast network dynamics, where more efficient adaptation reduces the spread of disease by targeting dangerous connections. Analysis of the bifurcation structure is supported by numerical simulations of disease spread on an adaptive network. The system displays a single parameter-dependent stable steady state and non-monotonic dependence of connectivity on link deactivation rate
Weakly coupled one-dimensional Mott insulators
We consider a model of one-dimensional Mott insulators coupled by a weak
interchain tunnelling . We first determine the single-particle Green's
function of a single chain by exact field-theoretical methods and then take the
tunnelling into account by means of a Random Phase Approximation (RPA). In
order to embed this approximation into a well-defined expansion with a small
parameter, the Fourier transform of the interchain coupling is
assumed to have a small support in momentum space such that every integration
over transverse wave vector yields a small factor . When
\tp(0) exceeds a critical value, a small Fermi surface develops in the form of
electron and hole pockets. We demonstrate that Luttinger's theorem holds both
in the insulating and in the metallic phases. We find that the quasi-particle
residue increases very fast through the transition and quickly reaches a
value of about . The metallic state close to the transition retains
many features of the one-dimensional system in the form of strong incoherent
continua.Comment: 14 pages, 13 figure
Process Evaluation of a Dutch Community Intervention to improve Health Related Behaviour in deprived neighbourhoods
Objectives: To assess whether a community intervention on health related behaviour in deprived neighbourhoods was delivered as planned and the extent of exposure to the intervention programme. Methods: Data were gathered throughout the intervention period using minutes of meetings, registration forms and a postal questionnaire among residents in intervention and comparison neighbourhoods. Results: Overall, the intervention was delivered according to the key principles of a "community approach", although community participation could have been improved. Neighbourhood coalitions organized more than 50 health related activities in the neighbourhoods over a two-year period. Most activities were directed at attracting attention, providing information, and increasing awareness and knowledge, and at changing behaviours. Programme awareness and programme participation were 24% respectively 3% among residents in the intervention neighbourhoods. Conclusions: The process evaluation indicated that it was feasible to implement a community intervention according to the key principles of the "community approach" in deprived neighbourhoods. However, it is unlikely that the total package of intervention activities had enough strength and sufficient exposure to attain community-wide health behaviour change
Fuzzy cluster validation using the partition negentropy criterion
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-04277-5_24Proceedings of the 19th International Conference, Limassol, Cyprus, September 14-17, 2009We introduce the Partition Negentropy Criterion (PNC) for cluster validation. It is a cluster validity index that rewards the average normality of the clusters, measured by means of the negentropy, and penalizes the overlap, measured by the partition entropy. The PNC is aimed at finding well separated clusters whose shape is approximately Gaussian. We use the new index to validate fuzzy partitions in a set of synthetic clustering problems, and compare the results to those obtained by the AIC, BIC and ICL criteria. The partitions are obtained by fitting a Gaussian Mixture Model to the data using the EM algorithm. We show that, when the real clusters are normally distributed, all the criteria are able to correctly assess the number of components, with AIC and BIC
allowing a higher cluster overlap. However, when the real cluster distributions are not Gaussian (i.e. the distribution assumed by the mixture model) the PNC outperforms the other indices, being able to correctly
evaluate the number of clusters while the other criteria (specially AIC and BIC) tend to overestimate it.This work has been partially supported with funds from
MEC BFU2006-07902/BFI, CAM S-SEM-0255-2006 and CAM/UAM project CCG08-UAM/TIC-442
Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection
Abstract. Histograms of oriented gradients (HOG) are widely employed image descriptors in modern computer-aided diagnosis systems. Built upon a set of local, robust statistics of low-level image gradients, HOG features are usually computed on raw intensity images. In this paper, we explore a learned image transformation scheme for producing higher-level inputs to HOG. Leveraging semantic object boundary cues, our methods compute data-driven image feature maps via a supervised boundary detector. Compared with the raw image map, boundary cues offer mid-level, more object-specific visual responses that can be suited for subsequent HOG encoding. We validate integrations of several image transformation maps with an application of computer-aided detection of lymph nodes on thoracoabdominal CT images. Our experiments demonstrate that semantic boundary cues based HOG descriptors complement and enrich the raw intensity alone. We observe an overall system with substantially improved results (∼78 % versus 60 % recall at 3 FP/volume for two target regions). The proposed system also moderately outperforms the state-of-the-art deep convolutional neural network (CNN) system in the mediastinum region, without relying on data augmentation and requiring significantly fewer training samples.
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