Search results for "Clustering"
showing 10 items of 446 documents
Mechanical Regulation of the Cytotoxic Activity of Natural Killer Cells
2020
AbstractMechanosensing has been recently explored for T cells and B cells and is believed to be part of their activation mechanism. Here, we explore the mechanosensing of the third type of lymphocytes – Natural Killer (NK) cells, by showing that they modulate their immune activity in response to changes in the stiffness of a stimulating surface. Interestingly, we found that this immune response is bell-shaped, and peaks for a stiffness of a few hundreds of kPa. This bell-shape behavior was observed only for surfaces functionalized with the activating ligand MHC class I polypeptide-related sequence A (MICA), but not for control surfaces lacking immunoactive functionalities. We found that sti…
Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps
2017
Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…
Graph Clustering with Local Density-Cut
2018
In this paper, we introduce a new graph clustering algorithm, called Dcut. The basic idea is to envision the graph clustering as a local density-cut problem. To identify meaningful communities in a graph, a density-connected tree is first constructed in a local fashion. Building upon the local intuitive density-connected tree, Dcut allows partitioning a graph into multiple densely tight-knit clusters effectively and efficiently. We have demonstrated that our method has several attractive benefits: (a) Dcut provides an intuitive criterion to evaluate the goodness of a graph clustering in a more precise way; (b) Building upon the density-connected tree, Dcut allows identifying high-quality cl…
Distributed Data Clustering via Opinion Dynamics
2015
We provide a distributed method to partition a large set of data in clusters, characterized by small in-group and large out-group distances. We assume a wireless sensors network in which each sensor is given a large set of data and the objective is to provide a way to group the sensors in homogeneous clusters by information type. In previous literature, the desired number of clusters must be specified a priori by the user. In our approach, the clusters are constrained to have centroids with a distance at least ε between them and the number of desired clusters is not specified. Although traditional algorithms fail to solve the problem with this constraint, it can help obtain a better cluste…
Problems and Techniques
2017
When biological networks are considered, the extraction of interesting knowledge often involves subgraphs isomorphism check that is known to be NP-complete. For this reason, many approaches try to simplify the problem under consideration by considering structures simpler than graphs, such as trees or paths. Furthermore, the number of existing approximate techniques is notably greater than the number of exact methods. In this chapter, we provide an overview of three important problems defined on biological networks: network alignment, network clustering, and motifs extraction from biological networks. For each of these problems, we also describe some of the most important techniques proposed…
Robust Synchronization-Based Graph Clustering
2013
Complex graph data now arises in various fields like social networks, protein-protein interaction networks, ecosystems, etc. To reveal the underlying patterns in graphs, an important task is to partition them into several meaningful clusters. The question is: how can we find the natural partitions of a complex graph which truly reflect the intrinsic patterns? In this paper, we propose RSGC, a novel approach to graph clustering. The key philosophy of RSGC is to consider graph clustering as a dynamic process towards synchronization. For each vertex, it is viewed as an oscillator and interacts with other vertices according to the graph connection information. During the process towards synchro…
The Burrows-Wheeler Transform between Data Compression and Combinatorics on Words
2013
The Burrows-Wheeler Transform (BWT) is a tool of fundamental importance in Data Compression and, recently, has found many applications well beyond its original purpose. The main goal of this paper is to highlight the mathematical and combinatorial properties on which the outstanding versatility of the $BWT$ is based, i.e. its reversibility and the clustering effect on the output. Such properties have aroused curiosity and fervent interest in the scientific world both for theoretical aspects and for practical effects. In particular, in this paper we are interested both to survey the theoretical research issues which, by taking their cue from Data Compression, have been developed in the conte…
Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks
2021
The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…
Cluster classification of dysphagia-oriented products considering flow, thixotropy and oscillatory testing
2011
Abstract The present paper proposes an objective classification of commercial thickened food widely used in patients with dysphagia. A total of 34 commercial enteral nutrition products were analyzed (beverages, main courses and desserts) corresponding to 6 different commercial brands. All these products contain different hydrocolloids (i.e., starch, xanthan gum, carrageenans, etc.) as thickeners, in order to get the desired texture. Joint consideration has been made of viscous behavior (flow and thixotropy) and viscoelastic behavior (oscillatory testing). Rheological measurements were fitted to different rheological and empirical mathematical models, and a total of 11 parameters were genera…
How Tick Size Affects the High Frequency Scaling of Stock Return Distributions
2014
We study the high frequency scaling of the distributions of returns for stocks traded at NASDAQ market as a function of the tick-to-price ratio. The tick-to-price ratio is a measure of an effective tick size. We find dramatic differences between distributions for assets with large and small tick-to-price ratio. The presence of returns clustering is evident for large tick size assets. The statistical differences between large and small tick size assets appear to reduce at higher time scales of observation. A possible way to explain returns dynamics for large tick size assets is the coupling of returns with bid-ask spread dynamics. A simple Markov- switching model is able to reproduce the pro…