Analysis of attractor distances in Random Boolean Networks

We study the properties of the distance between attractors in Random Boolean Networks, a prominent model of genetic regulatory networks. We define three distance measures, upon which attractor distance matrices are constructed and their main statistic parameters are computed. The experimental analysis shows that ordered networks have a very clustered set of attractors, while chaotic networks' attractors are scattered; critical networks show, instead, a pattern with characteristics of both ordered and chaotic networks.Comment: 9 pages, 6 figures. Presented at WIRN 2010 - Italian workshop on neural networks, May 2010. To appear in a volume published by IOS Pres

Evaluation of the stiffness tensor of a fractured medium with harmonic experiments

A fractured medium behaves as an anisotropic medium when the wavelength is much larger than the distance between fractures. These are modeled as boundary discontinuities in the displacement and particle velocity. When the set of fractures is plane, the theory predicts that the equivalent medium is transversely isotropic and viscoelastic (TIV). We present a novel procedure to determine the complex and frequency-dependent stiffness components. The methodology amounts to perform numerical compressibility and shear harmonic tests on a representative sample of the medium. These tests are described by a collection of elliptic boundary-value problems formulated in the space-frequency domain, which are solved with a Galerkin finite-element procedure. The examples illustrate the implementation of the tests to determine the set of stiffnesses and the associated phase velocities and quality factors.Fil: Santos, Juan Enrique. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto del Gas y del Petróleo; Argentina. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Benedettini, Stefano. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; ItaliaFil: Carcione, José M.. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Itali

Machine learning based data mining for Milky Way filamentary structures reconstruction

We present an innovative method called FilExSeC (Filaments Extraction, Selection and Classification), a data mining tool developed to investigate the possibility to refine and optimize the shape reconstruction of filamentary structures detected with a consolidated method based on the flux derivative analysis, through the column-density maps computed from Herschel infrared Galactic Plane Survey (Hi-GAL) observations of the Galactic plane. The present methodology is based on a feature extraction module followed by a machine learning model (Random Forest) dedicated to select features and to classify the pixels of the input images. From tests on both simulations and real observations the method appears reliable and robust with respect to the variability of shape and distribution of filaments. In the cases of highly defined filament structures, the presented method is able to bridge the gaps among the detected fragments, thus improving their shape reconstruction. From a preliminary "a posteriori" analysis of derived filament physical parameters, the method appears potentially able to add a sufficient contribution to complete and refine the filament reconstruction.Comment: Proceeding of WIRN 2015 Conference, May 20-22, Vietri sul Mare, Salerno, Italy. Published in Smart Innovation, Systems and Technology, Springer, ISSN 2190-3018, 9 pages, 4 figure

A randomized iterated greedy algorithm for the founder sequence reconstruction problem

The problem of inferring ancestral genetic information in terms of a set of founders of a given population arises in various biological contexts. In optimization terms, this problem can be formulated as a combinatorial string problem. The main problem of existing techniques, both exact and heuristic, is that their time complexity scales exponentially, which makes them impractical for solving large-scale instances. Basing our work on previous ideas outlined in [1], we developed a randomized iterated greedy algorithm that is able to provide good solutions in a short time span. The experimental evaluation shows that our algorithm is currently the best approximate technique, especially when large problem instances are concerned.Peer ReviewedPostprint (published version

In Situ Aerobic Biostimulation of Groundwater at a National Priority Site in Italy

Sarroch plant (CA, Italy) is an industrial area listed in the Italian Priority List of polluted sites. Pollution in groundwater has been addressed thanks to the design of a remediation action based on the aerobic biodegradation of petroleum hydrocarbons (predominantly mono-aromatic and short-chain aliphatic hydrocarbons) promoted by the injection of oxygen-releasing compounds. The feasibility of biostimulation at the site was preliminary assessed by means of laboratory tests. The direct push injection of the product has been foreseen at 2800 points, distributed along multiple lines perpendicular to the groundwater flow direction, over a total length of approximately 8 km and a total area of 90 hectares. According to the pollutant concentration measured in the different zones of the site, a different number of injection campaigns and injection frequency has been scheduled (3 to 10 campaigns, every 5 to 12 months). The estimated cost for the bioremediation action is 23 million Euros. Compared to the previous project approved in 2010, including a seafront physical barrier and groundwater circulation wells – in situ well stripping, the in situ injection of the oxygen-releasing compounds is an improvement toward a quicker, more effective and sustainable remediation of groundwater at the site. In view of all this, in 2017 the public authorities approved the variant of the project

Accounting for Post-Transcriptional Regulation in Boolean Networks Based Regulatory Models

Boolean Networks are emerging as a simple yet powerful for- malism to model and study Gene Regulatory Networks. Nevertheless, the most widely used Boolean Network-based models do not include any post-transcriptional regulation mechanism. In this paper we discuss how the post-transcriptional regulation mechanism mediated by miRNAs can be included in a Boolean Network based model to have a more realistic representation of a Gene Regulatory Networks. This contribution con- stitutes a critical preparatory step in the study of the topological and structural role of miRNAs in complex regulatory network

A study of the cold cores population in the Serpens star-forming region

As part of the Herschel Gould Belt survey, the Serpens star-forming region was observed with the Herschel PACS and SPIRE instruments. Data analysis is ongoing and a first version of the source catalog is ready; here we show some preliminary results

Distance biases in the estimation of the physical properties of Hi-GAL compact sources - I. Clump properties and the identification of high-mass star-forming candidates

The degradation of spatial resolution in star-forming regions, observed at large distances (d ≳ 1 kpc) with Herschel, can lead to estimates of the physical parameters of the detected compact sources (clumps), which do not necessarily mirror the properties of the original population of cores. This paper aims at quantifying the bias introduced in the estimation of these parameters by the distance effect. To do so, we consider Herschel maps of nearby star-forming regions taken from the Herschel Gould Belt survey, and simulate the effect of increased distance to understand what amount of information is lost when a distant star-forming region is observed with Herschel resolution. In the maps displaced to different distances we extract compact sources, and we derive their physical parameters as if they were original Herschel infrared Galactic Plane Survey maps of the extracted source samples. In this way, we are able to discuss how the main physical properties change with distance. In particular, we discuss the ability of clumps to form massive stars: we estimate the fraction of distant sources that are classified as high-mass stars-forming objects due to their position in the mass versus radius diagram, that are only 'false positives'. We also give a threshold for high-mass star formation M>1282 (r/ [pc])^{1.42} M_{☉}. In conclusion, this paper provides the astronomer dealing with Herschel maps of distant star-forming regions with a set of prescriptions to partially recover the character of the core population in unresolved clumps