Environmental path-entropy and collective motion

Inspired by the swarming or flocking of animal systems we study groups of agents moving in unbounded 2D space. Individual trajectories derive from a ``bottom-up'' principle: individuals reorient to maximise their future path entropy over environmental states. This can be seen as a proxy for keeping options open, a principle that may confer evolutionary fitness in an uncertain world. We find an ordered (co-aligned) state naturally emerges, as well as disordered states or rotating clusters; similar phenotypes are observed in birds, insects and fish, respectively. The ordered state exhibits an order-disorder transition under two forms of noise: (i) standard additive orientational noise, applied to the post-decision orientations (ii) ``cognitive'' noise, overlaid onto each individual's model of the future paths of other agents. Unusually, the order increases at low noise, before later decreasing through the order-disorder transition as the noise increases further.Comment: Accepted Phys. Rev. Lett. 28 March 202

Document Collection Visualization and Clustering Using An Atom Metaphor for Display and Interaction

Visual Data Mining have proven to be of high value in exploratory data analysis and data mining because it provides an intuitive feedback on data analysis and support decision-making activities. Several visualization techniques have been developed for cluster discovery such as Grand Tour, HD-Eye, Star Coordinates, etc. They are very useful tool which are visualized in 2D or 3D; however, they have not simple for users who are not trained. This thesis proposes a new approach to build a 3D clustering visualization system for document clustering by using k-mean algorithm. A cluster will be represented by a neutron (centroid) and electrons (documents) which will keep a distance with neutron by force. Our approach employs quantified domain knowledge and explorative observation as prediction to map high dimensional data onto 3D space for revealing the relationship among documents. User can perform an intuitive visual assessment of the consistency of the cluster structure

Mean field models for large data-clustering problems

We consider mean-field models for data--clustering problems starting from a generalization of the bounded confidence model for opinion dynamics. The microscopic model includes information on the position as well as on additional features of the particles in order to develop specific clustering effects. The corresponding mean--field limit is derived and properties of the model are investigated analytically. In particular, the mean--field formulation allows the use of a random subsets algorithm for efficient computations of the clusters. Applications to shape detection and image segmentation on standard test images are presented and discussed

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Active dumbbells: dynamics and morphology in the coexisting region

With the help of molecular dynamics simulations we study an ensemble of active dumbbells in purely repulsive interaction. We derive the phase diagram in the density-activity plane and we characterise the various phases with liquid, hexatic and solid character. The analysis of the structural and dynamical properties, such as enstrophy, mean square displacement, polarisation, and correlation functions, shows the continuous character of liquid and hexatic phases in the coexisting region when the activity is increased starting from the passive limit

Chimera Ligand for Pili and Lectin A Protein Controls Antibiotic-Promoted Biofilm Formation, Swarming Motility, Tolerance and Persister Formation by Pseudomonas aeruginosa

Throughout the human history, the fight against bacterial infections had never stopped but the remedies for bacterial infections were often insufficient and for many infectious diseases, there was no treatment available. The revolution in antimicrobial infection therapy began with the discovery of penicillin by Alexander Fleming in 1928. However, since the first introduction of antibiotics, bacteria over time have evolved sophisticated resistant strains against almost all the available antibiotics which cause selection pressure on the bacteria to evolve their genetic makeup and develop resistance against such agents. Furthermore, bacteria can form surface attached multicellular communities known as biofilms. Bacteria residing within biofilms are protected by biofilms which renders the bacteria more difficult to eliminate because of the low permeability of antibiotics through outer membranes. Combating such resistant bacteria is an extremely difficult task if using antibiotics alone. Hence scientific community continuously seeks new strategies to overpower these resistant bacteria. The focus of the research work presented here is to develop a class of chimera ligands that can bind to both pili and LecA protein of Pseudomonas aeruginosa to inhibit both swarming motility and biofilm formation. The potential adjuvant agents of these chimera ligands that can increase the effectiveness of antibiotics were demonstrated. In addition, the ability of our adjuvant molecules to eliminate drug-tolerant bacteria and to reduce persisters, in combination with antibiotics was demonstrated. The binding property of chimera ligands was demonstrated by competitive fluorescence polarization assay (LecA) and by adding a functional group to a ligand that can covalently attach to the receptor protein only when the physical ligand-receptor binding takes place (Pili). In addition, the effect of externally added pili on the swarming motility of Pseudomonas aeruginosa was tested to support the mechanistic study of the pili as the receptor (or one of the receptors) that will bind to rhamnolipids and our synthetic agents, and upon binding, causing the bacterial activities. For quantification of polysaccharides, two efficient detection and quantification methods that make use of the negative charges of the alginate polymer and do not involve degradation of the targeted polysaccharide were described. Both approaches provide efficient methods for monitoring alginate production by mucoid Pseudomonas aeruginosa. The effect of a class of synthetic analogs of rhamnolipids at controlling (promoting and inhibiting) the biofilm formation activities of a non-rhamnolipid-producing strain – rhlA – of Pseudomonas aeruginosa was demonstrated. The bioactive synthetic analogs of rhamnolipids promote biofilm formation by rhlA mutant at low concentrations but inhibit the biofilm formation at high concentrations. To explore the internal structures formed by the biofilms, the wild-type biofilms formed with substantial topography (hills and valleys) when the sample is under shaking conditions were observed by confocal microscope. Using this observation as a comparison, the effect of synthetic analogs of rhamnolipids on promoting structured (porous) biofilm of rhlA mutant, at intermediate concentrations between the low ones that promoted biofilm formation and the high ones that inhibited biofilm formation was demonstrated. This study suggests a potential chemical signaling approach to control multiple bacterial activities