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Velocity distribution in active particles systems.

ABSTRACT: We derive an analytic expression for the distribution of velocities of multiple interacting active particles which we test by numerical simulations. In clear contrast with equilibrium we find that the velocities are coupled to positions. Our model shows that, even for two particles only, the individual velocities display a variance depending on the interparticle separation and the emergence of correlations between the velocities of the particles. When considering systems composed of many particles we find an analytic expression connecting the overall velocity variance to density, at the mean-field level, and to the pair distribution function valid in the limit of small noise correlation times. Finally we discuss the intriguing analogies and main differences between our effective free energy functional and the theoretical scenario proposed so far for phase-separating active particles.

SUBMITTER: Marconi UM

PROVIDER: S-EPMC4802341 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Velocity distribution in active particles systems.

Marconi Umberto Marini Bettolo UM Gnan Nicoletta N Paoluzzi Matteo M Maggi Claudio C Di Leonardo Roberto R

Scientific reports 20160322

We derive an analytic expression for the distribution of velocities of multiple interacting active particles which we test by numerical simulations. In clear contrast with equilibrium we find that the velocities are coupled to positions. Our model shows that, even for two particles only, the individual velocities display a variance depending on the interparticle separation and the emergence of correlations between the velocities of the particles. When considering systems composed of many particl ...[more]

PMID: 27001289

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Project description:BACKGROUND:Eukaryotes are ubiquitous in natural environments such as soil and freshwater. Little is known of their presence in drinking water distribution systems (DWDSs) or of the environmental conditions that affect their activity and survival. METHODS:Eukaryotes were characterized by Illumina high-throughput sequencing targeting 18S rRNA gene (DNA) that estimates the total community and the 18S rRNA gene transcript (RNA) that is more representative of the active part of the community. DWDS cold water (N = 124), hot water (N = 40), and biofilm (N = 16) samples were collected from four cities in Finland. The sampled DWDSs were from two waterworks A-B with non-disinfected, recharged groundwater as source water and from three waterworks utilizing chlorinated water (two DWDSs of surface waterworks C-D and one of ground waterworks E). In each DWDS, samples were collected from three locations during four seasons of 1 year. RESULTS:A beta-diversity analysis revealed that the main driver shaping the eukaryotic communities was the DWDS (A-E) (R = 0.73, P < 0.001, ANOSIM). The kingdoms Chloroplastida (green plants and algae), Metazoa (animals: rotifers, nematodes), Fungi (e.g., Cryptomycota), Alveolata (ciliates, dinoflagellates), and Stramenopiles (algae Ochrophyta) were well represented and active-judging based on the rRNA gene transcripts-depending on the surrounding conditions. The unchlorinated cold water of systems (A-B) contained a higher estimated total number of taxa (Chao1, average 380-480) than chlorinated cold water in systems C-E (Chao1 ??210). Within each DWDS, unique eukaryotic communities were identified at different locations as was the case also for cold water, hot water, and biofilms. A season did not have a consistent impact on the eukaryotic community among DWDSs. CONCLUSIONS:This study comprehensively characterized the eukaryotic community members within the DWDS of well-maintained ground and surface waterworks providing good quality water. The study gives an indication that each DWDS houses a unique eukaryotic community, mainly dependent on the raw water source and water treatment processes in place at the corresponding waterworks. In particular, disinfection as well as hot water temperature seemed to represent a strong selection pressure that controlled the number of active eukaryotic species.

Dataset Information

Velocity distribution in active particles systems.

Publications

Velocity distribution in active particles systems.

Similar Datasets

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