84,237 research outputs found
Towards supporting interactions between self-managed cells
Accepted versio
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
Self-repair ability of evolved self-assembling systems in cellular automata
Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair
Statistical inference of the mechanisms driving collective cell movement
Numerous biological processes, many impacting on human health, rely on collective cell
movement. We develop nine candidate models, based on advection-diffusion partial differential equations, to describe various alternative mechanisms that may drive cell movement. The parameters of these models were inferred from one-dimensional projections of laboratory observations of Dictyostelium discoideum cells by sampling from the posterior distribution using the delayed rejection adaptive Metropolis algorithm (DRAM). The best model was selected using the Widely Applicable Information Criterion (WAIC). We conclude that cell movement in our study system was driven both by a self-generated gradient in an attractant that the cells could deplete locally, and by chemical interactions between the cells
A Framework to Manage the Complex Organisation of Collaborating: Its Application to Autonomous Systems
In this paper we present an analysis of the complexities of large group
collaboration and its application to develop detailed requirements for
collaboration schema for Autonomous Systems (AS). These requirements flow from
our development of a framework for collaboration that provides a basis for
designing, supporting and managing complex collaborative systems that can be
applied and tested in various real world settings. We present the concepts of
"collaborative flow" and "working as one" as descriptive expressions of what
good collaborative teamwork can be in such scenarios. The paper considers the
application of the framework within different scenarios and discuses the
utility of the framework in modelling and supporting collaboration in complex
organisational structures
Mobilization of Pollutant-Degrading Bacteria by Eukaryotic Zoospores
This study was supported by the Spanish Ministry of Science and Innovation (CGL2010-22068-C02-01 and CGL2013- 44554-R), the Andalusian Government (RNM 2337), and the CSIC JAE Program (RS). PvW has funding support from the BBSRC and NERC. Thanks are also given to Sara Hosseini of the Uppsala BioCenter, SLU, Uppsala, Sweden for a useful discussion on oomycete zoospores.Peer reviewedPostprin
Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids
Multicellular tumor spheroids are an important {\it in vitro} model of the
pre-vascular phase of solid tumors, for sizes well below the diagnostic limit:
therefore a biophysical model of spheroids has the ability to shed light on the
internal workings and organization of tumors at a critical phase of their
development. To this end, we have developed a computer program that integrates
the behavior of individual cells and their interactions with other cells and
the surrounding environment. It is based on a quantitative description of
metabolism, growth, proliferation and death of single tumor cells, and on
equations that model biochemical and mechanical cell-cell and cell-environment
interactions. The program reproduces existing experimental data on spheroids,
and yields unique views of their microenvironment. Simulations show complex
internal flows and motions of nutrients, metabolites and cells, that are
otherwise unobservable with current experimental techniques, and give novel
clues on tumor development and strong hints for future therapies.Comment: 20 pages, 10 figures. Accepted for publication in PLOS One. The
published version contains links to a supplementary text and three video
file
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