7,699 research outputs found
Relativistic tunneling through opaque barriers
We propose an analytical study of relativistic tunneling through opaque
barriers. We obtain a closed formula for the phase time. This formula is in
excellent agreement with the numerical simulations and corrects the standard
formula obtained by the stationary phase method. An important result is found
when the upper limit of the incoming energy distribution coincides with the
upper limit of the tunneling zone. In this case, the phase time is proportional
to the barrier width.Comment: 11 pages, 3 figure
Hunting for heavy composite Majorana neutrinos at the LHC
We investigate the search for heavy Majorana neutrinos stemming from a
composite model scenario at the upcoming LHC Run II at a center of mass energy
of 13 TeV. While previous studies of the composite Majorana neutrino were
focussed on gauge interactions via magnetic type transition coupling between
ordinary and heavy fermions (with mass ) here we complement the composite
model with contact interactions at the energy scale and we find that
the production cross sections are dominated by such contact interactions by
roughly two/three orders of magnitude. This mechanism provides therefore very
interesting rates at the prospected luminosities. We study the same sign
di-lepton and di-jet signature () and perform a fast
detector simulation based on Delphes. We compute 3 and 5
contour plots of the statistical significance in the parameter space
(). We find that the potentially excluded regions at TeV are quite larger than those excluded so far at Run I considering
searches with other signatures.Comment: 14 pages, 9 figures, Minor comments and few references added. Version
accepted by the European Physical Journal C (EPJC
Coupled DEM-LBM method for the free-surface simulation of heterogeneous suspensions
The complexity of the interactions between the constituent granular and
liquid phases of a suspension requires an adequate treatment of the
constituents themselves. A promising way for numerical simulations of such
systems is given by hybrid computational frameworks. This is naturally done,
when the Lagrangian description of particle dynamics of the granular phase
finds a correspondence in the fluid description. In this work we employ
extensions of the Lattice-Boltzmann Method for non-Newtonian rheology, free
surfaces, and moving boundaries. The models allows for a full coupling of the
phases, but in a simplified way. An experimental validation is given by an
example of gravity driven flow of a particle suspension
Some Salient Issues in Policy Evaluations of Urban Housing Markets
Housing problems are truly universal. For households the residential choice decision is basic both in view of its influence on their welfare and the substantial portion of their budget it claims. For regions and nations, housing determines centrally the investment sacrifices and has strong influences on the financial markets. These significances of housing problems have entailed a whole range of laws, regulations, and policies to afflict the functioning of the markets both from quantity and distributional aspects.
Different nations and regions have developed different arsenals of policy tools. Some attempts have been made to review and compare the national housing policies and the methods used in policy assessment. Such comparative studies are less common at the regional level.
The current Working Paper addresses the contemporary issues of policy evaluations of the working of urban housing markets by suggesting a conceptual framework for such analyses, based on systems analytic considerations. The paper contains a claim for the development of a new generation of housing market models for policy evaluations based on modern theories of probabilistic choice and structural change in dynamic systems. It provides an agenda for an international research project on urban housing policies at a time when management and renewal have replaced expansion as traits of urban fabric
Audio-Visual Pattern Recognition using HMM for Content-Based Multimedia Indexing
The aim of this work consists in the development of automatic techniques for the extraction of content-based information from audiovisual data. The focus has been placed on providing tools for analyzing both audio and visual streams, for translating the signal samples
into sequences of indices. The signal classification are performed by means of Hidden
Markov Models (HMM), used in an innovative approach: the input signal is considered as a non-stationary stochastic process, modeled by a HMM in which each state stands for a
different class of the signal. This defines an adaptive classification scheme for which a set of new training algorithms has been developed. Several samples from the MPEG-7 content set have been analyzed using the proposed classification scheme, demonstrating the performance of the overall approach to provide insights of the content of the audio-visual material
Expression of Bcl-2 in canine osteosarcoma
Osteosarcoma (OS) is the most common primary malignancy of bone. It is responsible for 80-85% of the primary bone tumors affecting dogs and it is characterized by aggressive and invasive behavior, with a high metastatic potential. Several studies on cancer and related tumorigenesis, show an involvement of the mechanisms of programmed cell death and cell survival. Many signals seem to be involved in the related mechanism of autophagy and in particular, our interest is focused on the expression of a family of Bcl-2 that seems to be involved either in the control of biomolecular mechanisms like autophagy and apoptosis. In this study we investigated the expression of Bcl-2 in different cases of spontaneous canine osteosarcoma and the related preliminary results are described. We found Bcl-2 activity was increased in OS tissue compared to normal bone tissue. These results suggested that Bcl-2 activity may play an important role in the formation of OS and as a diagnostic for neoplastic activity. However, further research is needed to confirm the role of Bcl-2 activity in OS in canines.Keywords: Autophagy, Bcl-2, Dog, Osteosarcom
Indoor radon survey in university buildings: a case study of Sapienza - University of Rome
The indoor radon concentration in underground workplaces pertaining to Sapienza – University of Rome have been monitored since the 90’s according to prescription of Italian Legislative Decree 230/95. In the last years, the recommendations contained in the Council Directive 2013/59/Euratom have shifted the focus to all indoor exposure situations by promoting actions to identify workplaces and dwellings with radon concentrations exceeding the reference level of 300 Bq/m3. In response to the upcoming transposition into national legislation, Sapienza has promoted the first Italian survey addressing workplaces in university buildings, regardless of the position with respect to the ground floor.
The survey has interested more than three hundred workplaces, i.e. administration and professors’ offices, research and educational laboratories, conference rooms and classrooms, distributed in fifteen different buildings. Places monitored are strongly heterogeneous in terms of users’ habit, occupancy pattern and building characteristics. The influence of these parameters into seasonal variation have been addressed by organizing the survey in four quarters. The indoor radon concentration is measured by solid state nuclear track detectors, CR39.
The aim of the paper is to present features, methods and intermediate results of the survey. The work, relying on the analysis of previous measurements interesting underground workplaces, focuses on methodology followed during all the preliminary and preparatory phases: active measurements by ionization chamber radon continuous monitor, radon progeny equilibrium factor estimations by radon daughters monitor, strategies for occupants’ awareness, positioning protocol and provisions to maximize representativity of results
Context Tree Selection: A Unifying View
The present paper investigates non-asymptotic properties of two popular
procedures of context tree (or Variable Length Markov Chains) estimation:
Rissanen's algorithm Context and the Penalized Maximum Likelihood criterion.
First showing how they are related, we prove finite horizon bounds for the
probability of over- and under-estimation. Concerning overestimation, no
boundedness or loss-of-memory conditions are required: the proof relies on new
deviation inequalities for empirical probabilities of independent interest. The
underestimation properties rely on loss-of-memory and separation conditions of
the process.
These results improve and generalize the bounds obtained previously. Context
tree models have been introduced by Rissanen as a parsimonious generalization
of Markov models. Since then, they have been widely used in applied probability
and statistics
Embedded Morphological Dilation Coding for 2D and 3D Images
Current wavelet-based image coders obtain high performance thanks to the identification and the exploitation of the statistical properties of natural images in the transformed domain. Zerotree-based algorithms, as Embedded Zerotree Wavelets (EZW) and Set Partitioning In Hierarchical Trees (SPIHT), offer high Rate-Distortion (RD) coding performance and low computational complexity by exploiting statistical dependencies among insignificant coefficients on hierarchical subband structures. Another possible approach tries to predict the clusters of significant coefficients by means of some form of morphological dilation. An example of a morphology-based coder is the Significance-Linked Connected Component Analysis (SLCCA) that has shown performance which are comparable to the zerotree-based coders but is not embedded. A new embedded bit-plane coder is proposed here based on morphological dilation of significant coefficients and context based arithmetic coding. The algorithm is able to exploit both intra-band and inter-band statistical dependencies among wavelet significant coefficients. Moreover, the same approach is used both for two and three-dimensional wavelet-based image compression. Finally we the algorithms are tested on some 2D images and on a medical volume, by comparing the RD results to those obtained with the state-of-the-art wavelet-based coders
Adaptive dilation analysis for wavelet coding with EMDC
The Embedded Morphological Dilation Coding (EMDC) algorithm, recently proposed by the author of this work, implements a direct coding of the wavelet coefficients significance map that is based on the action of a new kind of multiresolution binary (bit-plane) morphological operator. EMDC actually includes the most part of existing morphological wavelet codecs, it produces a fully progressive bitstream with low complexity and has demonstrated competitive coding performances. A peculiar feature of EMDC is the adaptive and the extended connectivity nature of the morphological analysis of the subband coefficients. In this paper we give a detailed description of this feature and quantify the related performance improvements. We conclude that the considered pattern analysis and coding technique allow an increased reduction of the data redundancy and fills the gap between existing morphological dilation techniques and state-of-the-art wavelet coders
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