205,207 research outputs found
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
PocketCare: Tracking the Flu with Mobile Phones using Partial Observations of Proximity and Symptoms
Mobile phones provide a powerful sensing platform that researchers may adopt
to understand proximity interactions among people and the diffusion, through
these interactions, of diseases, behaviors, and opinions. However, it remains a
challenge to track the proximity-based interactions of a whole community and
then model the social diffusion of diseases and behaviors starting from the
observations of a small fraction of the volunteer population. In this paper, we
propose a novel approach that tries to connect together these sparse
observations using a model of how individuals interact with each other and how
social interactions happen in terms of a sequence of proximity interactions. We
apply our approach to track the spreading of flu in the spatial-proximity
network of a 3000-people university campus by mobilizing 300 volunteers from
this population to monitor nearby mobile phones through Bluetooth scanning and
to daily report flu symptoms about and around them. Our aim is to predict the
likelihood for an individual to get flu based on how often her/his daily
routine intersects with those of the volunteers. Thus, we use the daily
routines of the volunteers to build a model of the volunteers as well as of the
non-volunteers. Our results show that we can predict flu infection two weeks
ahead of time with an average precision from 0.24 to 0.35 depending on the
amount of information. This precision is six to nine times higher than with a
random guess model. At the population level, we can predict infectious
population in a two-week window with an r-squared value of 0.95 (a random-guess
model obtains an r-squared value of 0.2). These results point to an innovative
approach for tracking individuals who have interacted with people showing
symptoms, allowing us to warn those in danger of infection and to inform health
researchers about the progression of contact-induced diseases
Ecological Modelling with the Calculus of Wrapped Compartments
The Calculus of Wrapped Compartments is a framework based on stochastic
multiset rewriting in a compartmentalised setting originally developed for the
modelling and analysis of biological interactions. In this paper, we propose to
use this calculus for the description of ecological systems and we provide the
modelling guidelines to encode within the calculus some of the main
interactions leading ecosystems evolution. As a case study, we model the
distribution of height of Croton wagneri, a shrub constituting the endemic
predominant species of the dry ecosystem in southern Ecuador. In particular, we
consider the plant at different altitude gradients (i.e. at different
temperature conditions), to study how it adapts under the effects of global
climate change.Comment: A preliminary version of this paper has been presented in CMC13 (LNCS
7762, pp 358-377, 2013
Biology of Applied Digital Ecosystems
A primary motivation for our research in Digital Ecosystems is the desire to
exploit the self-organising properties of biological ecosystems. Ecosystems are
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties have not been made explicit in Digital Ecosystems research.
Here, we discuss how biological properties contribute to the self-organising
features of biological ecosystems, including population dynamics, evolution, a
complex dynamic environment, and spatial distributions for generating local
interactions. The potential for exploiting these properties in artificial
systems is then considered. We suggest that several key features of biological
ecosystems have not been fully explored in existing digital ecosystems, and
discuss how mimicking these features may assist in developing robust, scalable
self-organising architectures. An example architecture, the Digital Ecosystem,
is considered in detail. The Digital Ecosystem is then measured experimentally
through simulations, with measures originating from theoretical ecology, to
confirm its likeness to a biological ecosystem. Including the responsiveness to
requests for applications from the user base, as a measure of the 'ecological
succession' (development).Comment: 9 pages, 4 figure, conferenc
Ecosystem-Oriented Distributed Evolutionary Computing
We create a novel optimisation technique inspired by natural ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
genes which are distributed in a peer-to-peer network, operating continuously
in time; this process feeds a second optimisation based on evolutionary
computing that operates locally on single peers and is aimed at finding
solutions to satisfy locally relevant constraints. We consider from the domain
of computer science distributed evolutionary computing, with the relevant
theory from the domain of theoretical biology, including the fields of
evolutionary and ecological theory, the topological structure of ecosystems,
and evolutionary processes within distributed environments. We then define
ecosystem- oriented distributed evolutionary computing, imbibed with the
properties of self-organisation, scalability and sustainability from natural
ecosystems, including a novel form of distributed evolu- tionary computing.
Finally, we conclude with a discussion of the apparent compromises resulting
from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with
arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102,
arXiv:0910.067
First-principles dynamics of electrons and phonons
First-principles calculations combining density functional theory and
many-body perturbation theory can provide microscopic insight into the dynamics
of electrons and phonons in materials. We review this theoretical and
computational framework, focusing on perturbative treatments of scattering,
dynamics and transport of coupled electrons and phonons. We discuss application
of these first-principles calculations to electronics, lighting, spectroscopy
and renewable energy.Comment: 14 pages, 1 figur
A rewiring model of intratumoral interaction networks.
Intratumoral heterogeneity (ITH) has been regarded as a key cause of the failure and resistance of cancer therapy, but how it behaves and functions remains unclear. Advances in single-cell analysis have facilitated the collection of a massive amount of data about genetic and molecular states of individual cancer cells, providing a fuel to dissect the mechanistic organization of ITH at the molecular, metabolic and positional level. Taking advantage of these data, we propose a computational model to rewire up a topological network of cell-cell interdependences and interactions that operate within a tumor mass. The model is grounded on the premise of game theory that each interactive cell (player) strives to maximize its fitness by pursuing a rational self-interest strategy, war or peace, in a way that senses and alters other cells to respond properly. By integrating this idea with genome-wide association studies for intratumoral cells, the model is equipped with a capacity to visualize, annotate and quantify how somatic mutations mediate ITH and the network of intratumoral interactions. Taken together, the model provides a topological flow by which cancer cells within a tumor cooperate or compete with each other to downstream pathogenesis. This topological flow can be potentially used as a blueprint for genetically intervening the pattern and strength of cell-cell interactions towards cancer control
A comparative analysis of parallel processing and super-individual methods for improving the computational performance of a large individual-based model
Individual-based modelling approaches are being used to simulate larger complex spatial systems in ecology and in other fields of research. Several novel model development issues now face researchers: in particular how to simulate large numbers of individuals with high levels of complexity, given finite computing resources. A case study of a spatially-explicit simulation of aphid population dynamics was used to assess two strategies for coping with a large number of individuals: the use of ‘super-individuals’ and parallel computing. Parallelisation of the model maintained the model structure and thus the simulation results were comparable to the original model. However, the super-individual implementation of the model caused significant changes to the model dynamics, both spatially and temporally. When super-individuals represented more than around 10 individuals it became evident that aggregate statistics generated from a super-individual model can hide more detailed deviations from an individual-level model. Improvements in memory use and model speed were perceived with both approaches. For the parallel approach, significant speed-up was only achieved when more than five processors were used and memory availability was only increased once five or more processors were used. The super-individual approach has potential to improve model speed and memory use dramatically, however this paper cautions the use of this approach for a density-dependent spatially-explicit model, unless individual variability is better taken into account
Morphometric differences in the grasshopper Cornops aquaticum (Bruner, 1906) from South America and South Africa
The semi-aquatic grasshopper Cornops aquaticum is native to South America and inhabits lowlands from southern Mexico to Central Argentina and Uruguay. It is host-specific to aquatic plants in the genera Eichhornia and Pontederia. A quarantine population has existed in South Africa for 10 y, and it is planned to release it there as a biological control agent of water hyacinth, E. crassipes. Various studies of C. aquaticum are coordinated under HICWA (www.mpil-ploen.mpg.de). This paper compares the morphometry of the release population and 11 native populations in South America. We tested four hypotheses: 1) South African and South American populations of C. aquaticum differ in morphology; 2) the South African laboratory population is more similar to other isolated populations in South America than to nonisolated populations; 3) morphology differs across sites; 4) morphology differs with host plant. South African populations differed from continental nonisolated populations, but not from continental isolated ones. Isolated populations presented smaller individuals than nonisolated, but there was also a change in male morphology: while in nonisolated populations male wing length was similar to their body length, in isolated populations, male wings were smaller than body length. Females were larger when on Eicchornia azurea than on E. crassipes, while males presented larger wings than their body on E. azurea, and similar lengths on E. crassipes. These morphological changes may have resulted from phenotypic plasticity, selection for small size, or because of a loss of genetic diversity in quantitative traits.Fil: Adis, Joachim. Institute for Limnology; AlemaniaFil: Sperber, Carlos F. Universidade Federal de Viçosa; BrasilFil: Brede, Edward G. Institute for Limnology; AlemaniaFil: Capello, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; ArgentinaFil: Franceschini, Maria Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Hill, Martin. Rhodes University; SudáfricaFil: Lhano, Marcos G. Universidade Federal de Viçosa; BrasilFil: Marques, Marinê. A;z M.. Universidade Federal de Mato Grosso; BrasilFil: Nunes, Ana L.. Muséu Paraense Emílio Goeldi; BrasilFil: Polar, Perry. CAB International; Trinidad y Tobag
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