6,692 research outputs found
Overview Of Nonlinear Kinetic Instabilities
The saturation of shear Alfven-like waves by alpha particles is presented from the general viewpoint of determining the saturation mechanisms of basic waves in a plasma destabilized by a perturbing source of free energy. The formalism is reviewed and then followed by analyses of isolated mode saturation far from and close to marginal stability. The effect of multiple waves that are isolated or are overlapping is then discussed. The presentation is concluded with a discussion of a non-conventional quasilinear theory that covers both extreme cases as well as the intermediate regime between the extremes.Physic
Metabolic Patterning on a Chip: Towards in vitro Liver Zonation of Primary Rat and Human Hepatocytes
An important number of healthy and diseased tissues shows spatial variations in their metabolic capacities across the tissue. The liver is a prime example of such heterogeneity where the gradual changes in various metabolic activities across the liver sinusoid is termed as “zonation” of the liver. Here, we introduce the Metabolic Patterning on a Chip (MPOC) platform capable of dynamically creating metabolic patterns across the length of a microchamber of liver tissue via actively enforced gradients of various metabolic modulators such as hormones and inducers. Using this platform, we were able to create continuous liver tissues of both rat and human origin with gradually changing metabolic activities. The gradients we have created in nitrogen, carbohydrate and xenobiotic metabolisms recapitulated an in vivo like zonation and zonal toxic response. Beyond its application in recapitulation of liver zonation in vitro as we demonstrate here, the MPOC platform can be used and expanded for a variety of purposes including better understanding of heterogeneity in many different tissues during developmental and adult stages
Progressive Hypoxia-on-a-chip: An In Vitro Oxygen Gradient Model for Capturing the Effects of Hypoxia on Primary Hepatocytes in Health and Disease
Oxygen is vital to the function of all tissues including the liver and lack of oxygen, that is, hypoxia can result in both acute and chronic injuries to the liver in vivo and ex vivo. Furthermore, a permanent oxygen gradient is naturally present along the liver sinusoid, which plays a role in the metabolic zonation and the pathophysiology of liver diseases. Accordingly, here, we introduce an in vitro microfluidic platform capable of actively creating a series of oxygen concentrations on a single continuous microtissue, ranging from normoxia to severe hypoxia. This range approximately captures both the physiologically relevant oxygen gradient generated from the portal vein to the central vein in the liver, and the severe hypoxia occurring in ischemia and liver diseases. Primary rat hepatocytes cultured in this microfluidic platform were exposed to an oxygen gradient of 0.3–6.9%. The establishment of an ascending hypoxia gradient in hepatocytes was confirmed in response to the decreasing oxygen supply. The hepatocyte viability in this platform decreased to approximately 80% along the hypoxia gradient. Simultaneously, a progressive increase in accumulation of reactive oxygen species and expression of hypoxia‐inducible factor 1α was observed with increasing hypoxia. These results demonstrate the induction of distinct metabolic and genetic responses in hepatocytes upon exposure to an oxygen (/hypoxia) gradient. This progressive hypoxia‐on‐a‐chip platform can be used to study the role of oxygen and hypoxia‐associated molecules in modeling healthy and injured liver tissues. Its use can be further expanded to the study of other hypoxic tissues such as tumors as well as the investigation of drug toxicity and efficacy under oxygen‐limited conditions
Nonlinear dispersion of stationary waves in collisionless plasmas
A nonlinear dispersion of a general stationary wave in collisionless plasma
is obtained in a non-differential form from a single-particle
oscillation-center Hamiltonian. For electrostatic oscillations in nonmagnetized
plasma, considered as a paradigmatic example, the linear dielectric function is
generalized, and the trapped particle contribution to the wave frequency shift
is found analytically as a function of the wave amplitude .
Smooth distributions yield , as usual. However,
beam-like distributions of trapped electrons result in different power laws, or
even a logarithmic nonlinearity, which are derived as asymptotic limits of the
same dispersion relation
RED-PSM: Regularization by Denoising of Partially Separable Models for Dynamic Imaging
Dynamic imaging addresses the recovery of a time-varying 2D or 3D object at
each time instant using its undersampled measurements. In particular, in the
case of dynamic tomography, only a single projection at a single view angle may
be available at a time, making the problem severely ill-posed. In this work, we
propose an approach, RED-PSM, which combines for the first time two powerful
techniques to address this challenging imaging problem. The first, are
partially separable models, which have been used to efficiently introduce a
low-rank prior for the spatio-temporal object. The second is the recent
Regularization by Denoising (RED), which provides a flexible framework to
exploit the impressive performance of state-of-the-art image denoising
algorithms, for various inverse problems. We propose a partially separable
objective with RED and a computationally efficient and scalable optimization
scheme with variable splitting and ADMM. Theoretical analysis proves the
convergence of our objective to a value corresponding to a stationary point
satisfying the first-order optimality conditions. Convergence is accelerated by
a particular projection-domain-based initialization. We demonstrate the
performance and computational improvements of our proposed RED-PSM with a
learned image denoiser by comparing it to a recent deep-prior-based method
known as TD-DIP. Although the main focus is on dynamic tomography, we also show
the performance advantages of RED-PSM in a cardiac dynamic MRI setting
Dynamic Tomography Reconstruction by Projection-Domain Separable Modeling
In dynamic tomography the object undergoes changes while projections are
being acquired sequentially in time. The resulting inconsistent set of
projections cannot be used directly to reconstruct an object corresponding to a
time instant. Instead, the objective is to reconstruct a spatio-temporal
representation of the object, which can be displayed as a movie. We analyze
conditions for unique and stable solution of this ill-posed inverse problem,
and present a recovery algorithm, validating it experimentally. We compare our
approach to one based on the recently proposed GMLR variation on deep prior for
video, demonstrating the advantages of the proposed approach
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