6,261 research outputs found
Regional Response Options to Global Climate Change
Global climate change has garnered some media attention, but has failed to gather the attention of most governmental decision makers and the public. In an effort to advance concerns about the issue, the New England Governors and Eastern Canadian Premiers sponsored a three-day symposium on climate change last May 19-21 in Portland. At the symposium, scientists and public officials from both the U.S. and Canada explored the science of climate change, the potential implications and impact of climate change on this region, and the possible policy responses. James Bruce [and Dean Marriott and Mark Victor, this issue] reflecting the breadth of topics explored at the symposium, argues that the level of public and public policy decision makers\u27 awareness about climate change issues must be heightened, and decision makers must begin to deal collaboratively with the many serious challenges climate change is presenting to the region
Long- and short-range correlations in the ab-initio no-core shell model
In the framework of the ab-initio no-core shell model (NCSM), we describe the
longitudinal-longitudinal distribution function, part of the inclusive (e,e')
longitudinal response. In the two-body cluster approximation, we compute the
effective operators consistent with the unitary transformation used to obtain
the effective Hamiltonian. When short-range correlations are probed, the
results display independence from the model space size and length scale.
Long-range correlations are more difficult to model in the NCSM and they can be
described only by increasing the model space or increasing the cluster size. In
order to illustrate the model space independence for short-range observables,
we present results for a large set of model spaces for 4He, and in 0-4hw model
spaces for 12C.Comment: 4 pages, 4 figure
The Role of Osteocytes in Targeted Bone Remodeling: A Mathematical Model
Until recently many studies of bone remodeling at the cellular level have
focused on the behavior of mature osteoblasts and osteoclasts, and their
respective precursor cells, with the role of osteocytes and bone lining cells
left largely unexplored. This is particularly true with respect to the
mathematical modeling of bone remodeling. However, there is increasing evidence
that osteocytes play important roles in the cycle of targeted bone remodeling,
in serving as a significant source of RANKL to support osteoclastogenesis, and
in secreting the bone formation inhibitor sclerostin. Moreover, there is also
increasing interest in sclerostin, an osteocyte-secreted bone formation
inhibitor, and its role in regulating local response to changes in the bone
microenvironment. Here we develop a cell population model of bone remodeling
that includes the role of osteocytes, sclerostin, and allows for the
possibility of RANKL expression by osteocyte cell populations. This model
extends and complements many of the existing mathematical models for bone
remodeling but can be used to explore aspects of the process of bone remodeling
that were previously beyond the scope of prior modeling work. Through numerical
simulations we demonstrate that our model can be used to theoretically explore
many of the most recent experimental results for bone remodeling, and can be
utilized to assess the effects of novel bone-targeting agents on the bone
remodeling process
Towards a New Spatial Representation of Bone Remodeling
Irregular bone remodeling is associated with a number of bone diseases such
as osteoporosis and multiple myeloma.
Computational and mathematical modeling can aid in therapy and treatment as
well as understanding fundamental biology. Different approaches to modeling
give insight into different aspects of a phenomena so it is useful to have an
arsenal of various computational and mathematical models.
Here we develop a mathematical representation of bone remodeling that can
effectively describe many aspects of the complicated geometries and spatial
behavior observed.
There is a sharp interface between bone and marrow regions. Also the surface
of bone moves in and out, i.e. in the normal direction, due to remodeling.
Based on these observations we employ the use of a level-set function to
represent the spatial behavior of remodeling. We elaborate on a temporal model
for osteoclast and osteoblast population dynamics to determine the change in
bone mass which influences how the interface between bone and marrow changes.
We exhibit simulations based on our computational model that show the motion
of the interface between bone and marrow as a consequence of bone remodeling.
The simulations show that it is possible to capture spatial behavior of bone
remodeling in complicated geometries as they occur \emph{in vitro} and \emph{in
vivo}.
By employing the level set approach it is possible to develop computational
and mathematical representations of the spatial behavior of bone remodeling. By
including in this formalism further details, such as more complex cytokine
interactions and accurate parameter values, it is possible to obtain
simulations of phenomena related to bone remodeling with spatial behavior much
as \emph{in vitro} and \emph{in vivo}. This makes it possible to perform
\emph{in silica} experiments more closely resembling experimental observations.Comment: Math. Biosci. Eng., 9(2), 201
Linking Cellular and Mechanical Processes in Articular Cartilage Lesion Formation: A Mathematical Model
A severe application of stress on articular cartilage can initiate a cascade
of biochemical reactions that can lead to the development of osteoarthritis. We
constructed a multiscale mathematical model of the process with three
components: cellular, chemical, and mechanical. The cellular component
describes the different chondrocyte states according to the chemicals these
cells release. The chemical component models the change in concentrations of
those chemicals. The mechanical component contains a simulation of pressure
application onto a cartilage explant and the resulting strains that initiate
the biochemical processes. The model creates a framework for incorporating
explicit mechanics, simulated by finite element analysis, into a theoretical
biology framework
Hysteresis, Avalanches, and Noise: Numerical Methods
In studying the avalanches and noise in a model of hysteresis loops we have
developed two relatively straightforward algorithms which have allowed us to
study large systems efficiently. Our model is the random-field Ising model at
zero temperature, with deterministic albeit random dynamics. The first
algorithm, implemented using sorted lists, scales in computer time as O(N log
N), and asymptotically uses N (sizeof(double)+ sizeof(int)) bits of memory. The
second algorithm, which never generates the random fields, scales in time as
O(N \log N) and asymptotically needs storage of only one bit per spin, about 96
times less memory than the first algorithm. We present results for system sizes
of up to a billion spins, which can be run on a workstation with 128MB of RAM
in a few hours. We also show that important physical questions were resolved
only with the largest of these simulations
Separation of Parallel Encoded Complex-Valued Slices (SPECS) From A Single Complex-Valued Aliased Coil Image
Purpose
Achieving a reduction in scan time with minimal inter-slice signal leakage is one of the significant obstacles in parallel MR imaging. In fMRI, multiband-imaging techniques accelerate data acquisition by simultaneously magnetizing the spatial frequency spectrum of multiple slices. The SPECS model eliminates the consequential inter-slice signal leakage from the slice unaliasing, while maintaining an optimal reduction in scan time and activation statistics in fMRI studies. Materials and Methods
When the combined k-space array is inverse Fourier reconstructed, the resulting aliased image is separated into the un-aliased slices through a least squares estimator. Without the additional spatial information from a phased array of receiver coils, slice separation in SPECS is accomplished with acquired aliased images in shifted FOV aliasing pattern, and a bootstrapping approach of incorporating reference calibration images in an orthogonal Hadamard pattern. Result
The aliased slices are effectively separated with minimal expense to the spatial and temporal resolution. Functional activation is observed in the motor cortex, as the number of aliased slices is increased, in a bilateral finger tapping fMRI experiment. Conclusion
The SPECS model incorporates calibration reference images together with coefficients of orthogonal polynomials into an un-aliasing estimator to achieve separated images, with virtually no residual artifacts and functional activation detection in separated images
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