20,394 research outputs found
MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation
MADNESS (multiresolution adaptive numerical environment for scientific
simulation) is a high-level software environment for solving integral and
differential equations in many dimensions that uses adaptive and fast harmonic
analysis methods with guaranteed precision based on multiresolution analysis
and separated representations. Underpinning the numerical capabilities is a
powerful petascale parallel programming environment that aims to increase both
programmer productivity and code scalability. This paper describes the features
and capabilities of MADNESS and briefly discusses some current applications in
chemistry and several areas of physics
A multi-phenotypic cancer model with cell plasticity
The conventional cancer stem cell (CSC) theory indicates a hierarchy of CSCs
and non-stem cancer cells (NSCCs), that is, CSCs can differentiate into NSCCs
but not vice versa. However, an alternative paradigm of CSC theory with
reversible cell plasticity among cancer cells has received much attention very
recently. Here we present a generalized multi-phenotypic cancer model by
integrating cell plasticity with the conventional hierarchical structure of
cancer cells. We prove that under very weak assumption, the nonlinear dynamics
of multi-phenotypic proportions in our model has only one stable steady state
and no stable limit cycle. This result theoretically explains the phenotypic
equilibrium phenomena reported in various cancer cell lines. Furthermore,
according to the transient analysis of our model, it is found that cancer cell
plasticity plays an essential role in maintaining the phenotypic diversity in
cancer especially during the transient dynamics. Two biological examples with
experimental data show that the phenotypic conversions from NCSSs to CSCs
greatly contribute to the transient growth of CSCs proportion shortly after the
drastic reduction of it. In particular, an interesting overshooting phenomenon
of CSCs proportion arises in three-phenotypic example. Our work may pave the
way for modeling and analyzing the multi-phenotypic cell population dynamics
with cell plasticity.Comment: 29 pages,6 figure
Harnessing Health Care Markets for the Public Interest: Insights for U.S. Health Reform From the German and Dutch Multipayer Systems
Outlines how the German and Dutch systems offer universal coverage via competing insurance plans and promote effective and efficient care. Highlights insurance exchanges, multipayer policies and group purchasing, information systems, and public reporting
Evolving generalist controllers to handle a wide range of morphological variations
Neuro-evolutionary methods have proven effective in addressing a wide range
of tasks. However, the study of the robustness and generalisability of evolved
artificial neural networks (ANNs) has remained limited. This has immense
implications in the fields like robotics where such controllers are used in
control tasks. Unexpected morphological or environmental changes during
operation can risk failure if the ANN controllers are unable to handle these
changes. This paper proposes an algorithm that aims to enhance the robustness
and generalisability of the controllers. This is achieved by introducing
morphological variations during the evolutionary process. As a results, it is
possible to discover generalist controllers that can handle a wide range of
morphological variations sufficiently without the need of the information
regarding their morphologies or adaptation of their parameters. We perform an
extensive experimental analysis on simulation that demonstrates the trade-off
between specialist and generalist controllers. The results show that
generalists are able to control a range of morphological variations with a cost
of underperforming on a specific morphology relative to a specialist. This
research contributes to the field by addressing the limited understanding of
robustness and generalisability in neuro-evolutionary methods and proposes a
method by which to improve these properties
- …