4,854 research outputs found
Current-Induced Step Bending Instability on Vicinal Surfaces
We model an apparent instability seen in recent experiments on current
induced step bunching on Si(111) surfaces using a generalized 2D BCF model,
where adatoms have a diffusion bias parallel to the step edges and there is an
attachment barrier at the step edge. We find a new linear instability with
novel step patterns. Monte Carlo simulations on a solid-on-solid model are used
to study the instability beyond the linear regime.Comment: 4 pages, 4 figure
The electron pressure in the atmospheres of late-type dwarfs
Over-ionization of potassium and sodium in late-type dwarf star
Effect of biochar and nitrogen on soil characteristics, growth and yield of radish (Raphanus sativus L.) at Paklihawa, Rupandehi condition of Nepal
An experiment on effect of biochar and nitrogen on soil characteristics, growth and yield of radish (Raphanus sativus L.) was conducted at Institute of Agriculture and Animal Science (IAAS), Paklihawa, Rupandehi, from November 2019 to February 2020. The experiment was laid in Randomized Complete Block Design with two factors: nitrogen and biochar, each factor having four levels (biochar: 0 t/ha, 5 t/ha, 10 t/ha and 15 t/ha and nitrogen: 0 kg/ha, 50 kg/ha, 100 kg/ha, 200 kg/ha), resulting in sixteen treatment combinations. Biochar application was found to be effective in improving soil bulk density, pH, soil organic matter and soil nitrogen and potassium content. Application of nitrogen fertilizer (200 kg/ha) and biochar (15 t/ha) alone, and in combination, showed significantly higher root dry matter (15.83 gm, 16.63 gm and 20.57 gm), biological yield (80 t/ha, 63.75 t/ha, and 95.75) and root yield (26.74 t/ha, 24.06 t/ha and 30.32 t/ha). In comparison to the sole effects of the highest dose of nitrogen fertilizer (200 kg/ha) and the highest dose of biochar (15 t/ha), their combined application showed the increased yield in radish root by 13.38% and 26.01%, respectively, indicating that the combined effect of biochar and nitrogen is more productive for the growth and yield in radish crop as compared to the sole effect of nitrogen and biochar
On generalized cluster algorithms for frustrated spin models
Standard Monte Carlo cluster algorithms have proven to be very effective for
many different spin models, however they fail for frustrated spin systems.
Recently a generalized cluster algorithm was introduced that works extremely
well for the fully frustrated Ising model on a square lattice, by placing bonds
between sites based on information from plaquettes rather than links of the
lattice. Here we study some properties of this algorithm and some variants of
it. We introduce a practical methodology for constructing a generalized cluster
algorithm for a given spin model, and investigate apply this method to some
other frustrated Ising models. We find that such algorithms work well for
simple fully frustrated Ising models in two dimensions, but appear to work
poorly or not at all for more complex models such as spin glasses.Comment: 34 pages in RevTeX. No figures included. A compressed postscript file
for the paper with figures can be obtained via anonymous ftp to
minerva.npac.syr.edu in users/paulc/papers/SCCS-527.ps.Z. Syracuse University
NPAC technical report SCCS-52
Dynamic behaviors in directed networks
Motivated by the abundance of directed synaptic couplings in a real
biological neuronal network, we investigate the synchronization behavior of the
Hodgkin-Huxley model in a directed network. We start from the standard model of
the Watts-Strogatz undirected network and then change undirected edges to
directed arcs with a given probability, still preserving the connectivity of
the network. A generalized clustering coefficient for directed networks is
defined and used to investigate the interplay between the synchronization
behavior and underlying structural properties of directed networks. We observe
that the directedness of complex networks plays an important role in emerging
dynamical behaviors, which is also confirmed by a numerical study of the
sociological game theoretic voter model on directed networks
Cluster update and recognition
We present a fast and robust cluster update algorithm that is especially
efficient in implementing the task of image segmentation using the method of
superparamagnetic clustering. We apply it to a Potts model with spin
interactions that are are defined by gray-scale differences within the image.
Motivated by biological systems, we introduce the concept of neural inhibition
to the Potts model realization of the segmentation problem. Including the
inhibition term in the Hamiltonian results in enhanced contrast and thereby
significantly improves segmentation quality. As a second benefit we can - after
equilibration - directly identify the image segments as the clusters formed by
the clustering algorithm. To construct a new spin configuration the algorithm
performs the standard steps of (1) forming clusters and of (2) updating the
spins in a cluster simultaneously. As opposed to standard algorithms, however,
we share the interaction energy between the two steps. Thus the update
probabilities are not independent of the interaction energies. As a
consequence, we observe an acceleration of the relaxation by a factor of 10
compared to the Swendson and Wang procedure.Comment: 4 pages, 2 figure
Evaluation of Foliar Fungicides on Soybeans in 2018
Soybean foliar fungicides were evaluated for foliar disease management and yield response across seven Iowa State University research and demonstration farms in 2018. These included the Northwest Research and Demonstration Farm(Sutherland), Northern Research and Demonstration Farm (Kanawha), Northeast Research and Demonstration Farm(Nashua), Central Iowa Research Farms (Ames), Armstrong Memorial Research and Demonstration Farm (Lewis), McNay Memorial Research and Demonstration Farm (Chariton), and Southeast Research and Demonstration Farm(Crawfordsville)
On U_q(SU(2))-symmetric Driven Diffusion
We study analytically a model where particles with a hard-core repulsion
diffuse on a finite one-dimensional lattice with space-dependent, asymmetric
hopping rates. The system dynamics are given by the
\mbox{U[SU(2)]}-symmetric Hamiltonian of a generalized anisotropic
Heisenberg antiferromagnet. Exploiting this symmetry we derive exact
expressions for various correlation functions. We discuss the density profile
and the two-point function and compute the correlation length as well
as the correlation time . The dynamics of the density and the
correlations are shown to be governed by the energy gaps of a one-particle
system. For large systems and depend only on the asymmetry. For
small asymmetry one finds indicating a dynamical exponent
as for symmetric diffusion.Comment: 10 pages, LATE
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