59,960 research outputs found
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
Engineering simulations for cancer systems biology
Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions
Competencies, Technological Change and Network Dynamics. The case of the bio-pharmaceutical industry
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Modeling the scaling properties of human mobility
While the fat tailed jump size and the waiting time distributions
characterizing individual human trajectories strongly suggest the relevance of
the continuous time random walk (CTRW) models of human mobility, no one
seriously believes that human traces are truly random. Given the importance of
human mobility, from epidemic modeling to traffic prediction and urban
planning, we need quantitative models that can account for the statistical
characteristics of individual human trajectories. Here we use empirical data on
human mobility, captured by mobile phone traces, to show that the predictions
of the CTRW models are in systematic conflict with the empirical results. We
introduce two principles that govern human trajectories, allowing us to build a
statistically self-consistent microscopic model for individual human mobility.
The model not only accounts for the empirically observed scaling laws but also
allows us to analytically predict most of the pertinent scaling exponents
Foot and mouth disease in Zambia: Spatial and temporal distributions of outbreaks, assessment of clusters and implications for control
Zambia has been experiencing low livestock productivity as well as trade restrictions owing to the occurrence of foot and mouth disease (FMD), but little is known about the epidemiology of the disease in these endemic settings. The fundamental questions relate to the spatio-temporal distribution of FMD cases and what determines their occurrence. A retrospective review of FMD cases in Zambia from 1981 to 2012 was conducted using geographical information systems and the SaTScan software package. Information was collected from peer-reviewed journal articles, conference proceedings, laboratory reports, unpublished scientific reports and grey literature. A spaceâtime permutation probability model using a varying time window of one year was used to scan for areas with high infection rates. The spatial scan statistic detected a significant purely spatial cluster around the MbalaâIsoka area between 2009 and 2012, with secondary clusters in SeshekeâKazungula in 2007 and 2008, the Kafue flats in 2004 and 2005 and Livingstone in 2012. This study provides evidence of the existence of statistically significant FMD clusters and an increase in occurrence in Zambia between 2004 and 2012. The identified clusters agree with areas known to be at high risk of FMD. The FMD virus transmission dynamics and the heterogeneous variability in risk within these locations may need further investigation
A mathematical model of systemic inhibition of angiogenesis in metastatic development
We present a mathematical model describing the time development of a
population of tumors subject to mutual angiogenic inhibitory signaling. Based
on biophysical derivations, it describes organism-scale population dynamics
under the influence of three processes: birth (dissemination of secondary
tumors), growth and inhibition (through angiogenesis). The resulting model is a
nonlinear partial differential transport equation with nonlocal boundary
condition. The nonlinearity stands in the velocity through a nonlocal quantity
of the model (the total metastatic volume). The asymptotic behavior of the
model is numerically investigated and reveals interesting dynamics ranging from
convergence to a steady state to bounded non-periodic or periodic behaviors,
possibly with complex repeated patterns. Numerical simulations are performed
with the intent to theoretically study the relative impact of potentiation or
impairment of each process of the birth/growth/inhibition balance. Biological
insights on possible implications for the phenomenon of "cancer without
disease" are also discussed
Compressed Sensing - A New mode of Measurement
After introducing the concept of compressed sensing as a complementary
measurement mode to the classical Shannon-Nyquist approach, I discuss some of
the drivers, potential challenges and obstacles to its implementation. I end with a
speculative attempt to embed compressed sensing as an enabling methodology
within the emergence of data-driven discovery. As a consequence I predict the
growth of non-nomological sciences where heuristic correlations will find
applications but often bypass conventional pure basic and use-inspired basic
research stages due to the lack of verifiable hypotheses
Quantitative modelling of the humanâEarth System a new kind of science?
The five grand challenges set out for Earth System Science by the International Council for Science in 2010 require a true fusion of social science, economics and natural scienceâa fusion that has not yet been achieved. In this paper we propose that constructing quantitative models of the dynamics of the humanâEarth system can serve as a catalyst for this fusion. We confront well-known objections to modelling societal dynamics by drawing lessons from the development of natural science over the last four centuries and applying them to social and economic science. First, we pose three questions that require real integration of the three fields of science. They concern the coupling of physical planetary boundaries via social processes; the extension of the concept of planetary boundaries to the humanâEarth System; and the possibly self-defeating nature of the United Nationâs Millennium Development Goals. Second, we ask whether there are regularities or âattractorsâ in the humanâEarth System analogous to those that prompted the search for laws of nature. We nominate some candidates and discuss why we should observe them given that human actors with foresight and intentionality play a fundamental role in the humanâEarth System. We conclude that, at sufficiently large time and space scales, social processes are predictable in some sense. Third, we canvass some essential mathematical techniques that this research fusion must incorporate, and we ask what kind of data would be needed to validate or falsify our models. Finally, we briefly review the state of the art in quantitative modelling of the humanâEarth System today and highlight a gap between so-called integrated assessment models applied at regional and global scale, which could be filled by a new scale of model
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