3,625 research outputs found
Effect of the orientational relaxation on the collective motion of patterns formed by self-propelled particles
We investigate the collective behavior of self-propelled particles (SPPs)
undergoing competitive processes of pattern formation and rotational relaxation
of their self-propulsion velocities. In full accordance with previous work, we
observe transitions between different steady states of the SPPs caused by the
intricate interplay among the involved effects of pattern formation,
orientational order, and coupling between the SPP density and orientation
fields. Based on rigorous analytical and numerical calculations, we prove that
the rate of the orientational relaxation of the SPP velocity field is the main
factor determining the steady states of the SPP system. Further, we determine
the boundaries between domains in the parameter plane that delineate
qualitatively different resting and moving states. In addition, we analytically
calculate the collective velocity of the SPPs and show that it
perfectly agrees with our numerical results. We quantitatively demonstrate that
does not vanish upon approaching the transition boundary between the
moving pattern and homogeneous steady states.Comment: 3 Figure
A plasma solenoid driven by an Orbital Angular Momentum laser beam
A tens of Tesla quasi-static axial magnetic field can be produced in the
interaction of a short intense laser beam carrying an Orbital Angular Momentum
with an underdense plasma. Three-dimensional "Particle In Cell" simulations and
analytical model demonstrate that orbital angular momentum is transfered from a
tightly focused radially polarized laser beam to electrons without any
dissipative effect. A theoretical model describing the balistic interaction of
electrons with laser shows that particles gain angular velocity during their
radial and longitudinal drift in the laser field. The agreement between PIC
simulations and the simplified model identifies routes to increase the
intensity of the solenoidal magnetic field by controlling the orbital angular
momentum and/or the energy of the laser beam
Thin film evolution equations from (evaporating) dewetting liquid layers to epitaxial growth
In the present contribution we review basic mathematical results for three
physical systems involving self-organising solid or liquid films at solid
surfaces. The films may undergo a structuring process by dewetting,
evaporation/condensation or epitaxial growth, respectively. We highlight
similarities and differences of the three systems based on the observation that
in certain limits all of them may be described using models of similar form,
i.e., time evolution equations for the film thickness profile. Those equations
represent gradient dynamics characterized by mobility functions and an
underlying energy functional.
Two basic steps of mathematical analysis are used to compare the different
system. First, we discuss the linear stability of homogeneous steady states,
i.e., flat films; and second the systematics of non-trivial steady states,
i.e., drop/hole states for dewetting films and quantum dot states in epitaxial
growth, respectively. Our aim is to illustrate that the underlying solution
structure might be very complex as in the case of epitaxial growth but can be
better understood when comparing to the much simpler results for the dewetting
liquid film. We furthermore show that the numerical continuation techniques
employed can shed some light on this structure in a more convenient way than
time-stepping methods.
Finally we discuss that the usage of the employed general formulation does
not only relate seemingly not related physical systems mathematically, but does
as well allow to discuss model extensions in a more unified way
Enhancement of laser-driven ion acceleration in non-periodic nanostructured targets
Using particle-in-cell simulations, we demonstrate an improvement of the
target normal sheath acceleration (TNSA) of protons in non-periodically
nanostructured targets with micron-scale thickness. Compared to standard flat
foils, an increase in the proton cutoff energy by up to a factor of two is
observed in foils coated with nanocones or perforated with nanoholes. The
latter nano-perforated foils yield the highest enhancement, which we show to be
robust over a broad range of foil thicknesses and hole diameters. The
improvement of TNSA performance results from more efficient hot-electron
generation, caused by a more complex laser-electron interaction geometry and
increased effective interaction area and duration. We show that TNSA is
optimized for a nanohole distribution of relatively low areal density and that
is not required to be periodic, thus relaxing the manufacturing constraints.Comment: 11 pages, 8 figure
The relation of steady evaporating drops fed by an influx and freely evaporating drops
We discuss a thin film evolution equation for a wetting evaporating liquid on
a smooth solid substrate. The model is valid for slowly evaporating small
sessile droplets when thermal effects are insignificant, while wettability and
capillarity play a major role. The model is first employed to study steady
evaporating drops that are fed locally through the substrate. An asymptotic
analysis focuses on the precursor film and the transition region towards the
bulk drop and a numerical continuation of steady drops determines their fully
non-linear profiles.
Following this, we study the time evolution of freely evaporating drops
without influx for several initial drop shapes. As a result we find that drops
initially spread if their initial contact angle is larger than the apparent
contact angle of large steady evaporating drops with influx. Otherwise they
recede right from the beginning
Note on the hydrodynamic description of thin nematic films: strong anchoring model
We discuss the long-wave hydrodynamic model for a thin film of nematic liquid
crystal in the limit of strong anchoring at the free surface and at the
substrate. We rigorously clarify how the elastic energy enters the evolution
equation for the film thickness in order to provide a solid basis for further
investigation: several conflicting models exist in the literature that predict
qualitatively different behaviour. We consolidate the various approaches and
show that the long-wave model derived through an asymptotic expansion of the
full nemato-hydrodynamic equations with consistent boundary conditions agrees
with the model one obtains by employing a thermodynamically motivated gradient
dynamics formulation based on an underlying free energy functional. As a
result, we find that in the case of strong anchoring the elastic distortion
energy is always stabilising. To support the discussion in the main part of the
paper, an appendix gives the full derivation of the evolution equation for the
film thickness via asymptotic expansion
Quantitative assignment of reaction directionality in a multicompartmental human metabolic reconstruction.
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files.
This article is open access.Reaction directionality is a key constraint in the modeling of genome-scale metabolic networks. We thermodynamically constrained reaction directionality in a multicompartmental genome-scale model of human metabolism, Recon 1, by calculating, in vivo, standard transformed reaction Gibbs energy as a function of compartment-specific pH, electrical potential, and ionic strength. We show that compartmental pH is an important determinant of thermodynamically determined reaction directionality. The effects of pH on transport reaction thermodynamics are only seen to their full extent when metabolites are represented as pseudoisomer groups of multiple protonated species. We accurately predict the irreversibility of 387 reactions, with detailed propagation of uncertainty in input data, and manually curate the literature to resolve conflicting directionality assignments. In at least half of all cases, a prediction of a reversible reaction directionality is due to the paucity of compartment-specific quantitative metabolomic data, with remaining cases due to uncertainty in estimation of standard reaction Gibbs energy. This study points to the pressing need for 1), quantitative metabolomic data, and 2), experimental measurement of thermochemical properties for human metabolites.Icelandic Research Fund/00406022
eu-repo/grantAgreement/EC/FP7/23281
Computationally efficient flux variability analysis
<p>Abstract</p> <p>Background</p> <p>Flux variability analysis is often used to determine robustness of metabolic models in various simulation conditions. However, its use has been somehow limited by the long computation time compared to other constraint-based modeling methods.</p> <p>Results</p> <p>We present an open source implementation of flux variability analysis called fastFVA. This efficient implementation makes large-scale flux variability analysis feasible and tractable allowing more complex biological questions regarding network flexibility and robustness to be addressed.</p> <p>Conclusions</p> <p>Networks involving thousands of biochemical reactions can be analyzed within seconds, greatly expanding the utility of flux variability analysis in systems biology.</p
Whole-body metabolic modelling predicts isoleucine dependency of SARS-CoV-2 replication
We aimed at investigating host-virus co-metabolism during SARS-CoV-2 infection. Therefore, we extended comprehensive sex-specific, whole-body organ resolved models of human metabolism with the necessary reactions to replicate SARS-CoV-2 in the lung as well as selected peripheral organs. Using this comprehensive host-virus model, we obtained the following key results: 1. The predicted maximal possible virus shedding rate was limited by isoleucine availability. 2. The supported initial viral load depended on the increase in CD4+ T-cells, consistent with the literature. 3. During viral infection, the whole-body metabolism changed including the blood metabolome, which agreed well with metabolomic studies from COVID-19 patients and healthy controls. 4. The virus shedding rate could be reduced by either inhibition of the guanylate kinase 1 or availability of amino acids, e.g., in the diet. 5. The virus variants differed in their maximal possible virus shedding rates, which could be inversely linked to isoleucine occurrences in the sequences. Taken together, this study presents the metabolic crosstalk between host and virus and emphasises the role of amino acid metabolism during SARS-CoV-2 infection, in particular of isoleucine. As such, it provides an example of how computational modelling can complement more canonical approaches to gain insight into host-virus crosstalk and to identify potential therapeutic strategies.Analytical BioScience
A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1
<p>Abstract</p> <p>Background</p> <p>Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human reconstructions. They raise the question if the various successful applications of microbial reconstructions can be replicated in complex organisms.</p> <p>Results</p> <p>We mapped the published, detailed reconstruction of human metabolism (Recon 1) to other mammals. By searching for genes homologous to Recon 1 genes within mammalian genomes, we were able to create draft metabolic reconstructions of five mammals, including the mouse. Each draft reconstruction was created in compartmentalized and non-compartmentalized version via two different approaches. Using gap-filling algorithms, we were able to produce all cellular components with three out of four versions of the mouse metabolic reconstruction. We finalized a functional model by iterative testing until it passed a predefined set of 260 validation tests. The reconstruction is the largest, most comprehensive mouse reconstruction to-date, accounting for 1,415 genes coding for 2,212 gene-associated reactions and 1,514 non-gene-associated reactions.</p> <p>We tested the mouse model for phenotype prediction capabilities. The majority of predicted essential genes were also essential in vivo. However, our non-tissue specific model was unable to predict gene essentiality for many of the metabolic genes shown to be essential in vivo. Our knockout simulation of the lipoprotein lipase gene correlated well with experimental results, suggesting that softer phenotypes can also be simulated.</p> <p>Conclusions</p> <p>We have created a high-quality mouse genome-scale metabolic reconstruction, iMM1415 (<it>Mus Musculus</it>, 1415 genes). We demonstrate that the mouse model can be used to perform phenotype simulations, similar to models of microbe metabolism. Since the mouse is an important experimental organism, this model should become an essential tool for studying metabolic phenotypes in mice, including outcomes from drug screening.</p
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