A Topological Framework for the Computation of the HOMFLY Polynomial and Its Application to Proteins

Polymers can be modeled as open polygonal paths and their closure generates knots. Knotted proteins detection is currently achieved via high-throughput methods based on a common framework insensitive to the handedness of knots. Here we propose a topological framework for the computation of the HOMFLY polynomial, an handedness-sensitive invariant. Our approach couples a multi-component reduction scheme with the polynomial computation. After validation on tabulated knots and links the framework was applied to the entire Protein Data Bank along with a set of selected topological checks that allowed to discard artificially entangled structures. This led to an up-to-date table of knotted proteins that also includes two newly detected right-handed trefoil knots in recently deposited protein structures. The application range of our framework is not limited to proteins and it can be extended to the topological analysis of biological and synthetic polymers and more generally to arbitrary polygonal paths.Comment: 20 pages, 7 figure

Cooperative Spectrum Sensing based on the Limiting Eigenvalue Ratio Distribution in Wishart Matrices

Recent advances in random matrix theory have spurred the adoption of eigenvalue-based detection techniques for cooperative spectrum sensing in cognitive radio. Most of such techniques use the ratio between the largest and the smallest eigenvalues of the received signal covariance matrix to infer the presence or absence of the primary signal. The results derived so far in this field are based on asymptotical assumptions, due to the difficulties in characterizing the exact distribution of the eigenvalues ratio. By exploiting a recent result on the limiting distribution of the smallest eigenvalue in complex Wishart matrices, in this paper we derive an expression for the limiting eigenvalue ratio distribution, which turns out to be much more accurate than the previous approximations also in the non-asymptotical region. This result is then straightforwardly applied to calculate the decision threshold as a function of a target probability of false alarm. Numerical simulations show that the proposed detection rule provides a substantial performance improvement compared to the other eigenvalue-based algorithms.Comment: 7 pages, 2 figures, submitted to IEEE Communications Letter

Focal Firms as Technological Gatakeepers within Industrial Districts Knowledge Creation and Dissemination in the Italian Packaging Machinery Industry

Despite the diffusion of communication tools and boundary spanning technologies, knowledge flows in innovation processes retain a distinct localized nature in many industries and geographical clusters emerge as critical areas to foster technological diffusion. In this paper we focus on the role of focal firms in industrial clusters as “gatekeepers” introducing external technological novelties in the cluster and enacting new useful knowledge production locally, thus enhancing international competitive capabilities of all firms in the cluster. We analyze a longitudinal dataset of 720 patents 1 Corresponding Author www.druid.dk granted by USPTO between 1990 and 2003 to firms in the automatic packaging machinery industrial district of Emilia-Romagna in Northern Italy, and a matched-sample to control for the uneven geographical distribution of R&D and patenting activities. Our results show that firms within the cluster use local knowledge to a greater extent and more rapidly than knowledge from the outside than it would be expected given the geographic distribution of innovative activity in the industry. Moreover, focal firms use external knowledge to a greater extent than other firms operating in the cluster, and other (non focal) firms within the cluster use knowledge from focal firms to a greater extent than would be expected given the geographic distribution of innovative activity in the industry. Implications for research on the geographical distribution of innovation activities are discussed.Innovation processes, Knowledge flows, Geographical clusters

A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies

Adaptive robotic ecologies are networks of heterogeneous robotic devices (sensors, actuators, automated appliances) pervasively embedded in everyday environments, where they learn to cooperate towards the achievement of complex tasks. While their flexibility makes them an increasingly popular way to improve a system’s reliability, scalability, robustness and autonomy, their effective realisation demands integrated control and software solutions for the specification, integration and management of their highly heterogeneous and computational constrained components. In this extended abstract we briefly illustrate the characteristic requirements dictated by robotic ecologies, discuss our experience in developing adaptive robotic ecologies, and provide an overview of the specific solutions developed as part of the EU FP7 RUBICON Project

Language Interaction and Quality Issues: An Exploratory Study

Most software systems are complex and often composed of a large number of artifacts. To realize each different artifacts specific techniques are used resorting on different abstractions, languages and tools. Successful composition of different elements requires coherence among them. Unfortunately constraints between artifacts written in different languages are usually not formally expressed neither checked by supporting tools; as consequence they can be a source of problems. In this paper we explore the role of the relations between artifacts written in different languages by means of a case study on the Hadoop open source project. We present the problem introducing the related terminology, we quantify the phenomenon and investigate the relation with defect pronenes

Rknots: topological analysis of knotted biopolymers with R

Motivation: Rknots is a flexible R package providing tools for the detection and characterization of topological knots in biological polymers. The package is well documented and provides a simple syntax for data import and preprocessing, structure reduction, topological analyses and 2D and 3D visualization. Remarkably, Rknots is not limited to protein knots and allows researchers from interdisciplinary fields to analyze different topological structures and to develop simple yet fully custom pipelines. Availability: Rknots is distributed under the GPL-2 license and is available from the CRAN (the Comprehensive R Archive network) at http://cran.r-project.org/web/packages/Rknots Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics onlin