16,194 research outputs found
Superheat: An R package for creating beautiful and extendable heatmaps for visualizing complex data
The technological advancements of the modern era have enabled the collection
of huge amounts of data in science and beyond. Extracting useful information
from such massive datasets is an ongoing challenge as traditional data
visualization tools typically do not scale well in high-dimensional settings.
An existing visualization technique that is particularly well suited to
visualizing large datasets is the heatmap. Although heatmaps are extremely
popular in fields such as bioinformatics for visualizing large gene expression
datasets, they remain a severely underutilized visualization tool in modern
data analysis. In this paper we introduce superheat, a new R package that
provides an extremely flexible and customizable platform for visualizing large
datasets using extendable heatmaps. Superheat enhances the traditional heatmap
by providing a platform to visualize a wide range of data types simultaneously,
adding to the heatmap a response variable as a scatterplot, model results as
boxplots, correlation information as barplots, text information, and more.
Superheat allows the user to explore their data to greater depths and to take
advantage of the heterogeneity present in the data to inform analysis
decisions. The goal of this paper is two-fold: (1) to demonstrate the potential
of the heatmap as a default visualization method for a wide range of data types
using reproducible examples, and (2) to highlight the customizability and ease
of implementation of the superheat package in R for creating beautiful and
extendable heatmaps. The capabilities and fundamental applicability of the
superheat package will be explored via three case studies, each based on
publicly available data sources and accompanied by a file outlining the
step-by-step analytic pipeline (with code).Comment: 26 pages, 10 figure
Magnetic Interactions in BiFeO: a First-Principles Study
First-principles calculations, in combination with the four-state energy
mapping method, are performed to extract the magnetic interaction parameters of
multiferroic BiFeO. Such parameters include the symmetric exchange (SE)
couplings and the Dzyaloshinskii-Moriya (DM) interactions up to second nearest
neighbors, as well as the single ion anisotropy (SIA). All magnetic parameters
are obtained not only for the structural ground state, but also for the
and phases in order to determine the effects of
ferroelectricity and antiferrodistortion distortions, respectively, on these
magnetic parameters. In particular, two different second-nearest neighbor
couplings are identified and their origins are discussed in details. Moreover,
Monte-Carlo (MC) simulations using a magnetic Hamiltonian incorporating these
first-principles-derived interaction parameters are further performed. They
result (i) not only in the accurate prediction of the spin-canted G-type
antiferromagnetic structure and of the known magnetic cycloid propagating along
a direction, as well as their unusual characteristics (such
as a weak magnetization and spin-density-waves, respectively); (ii) but also in
the finding of another cycloidal state of low-energy and that awaits to be
experimentally confirmed. Turning on and off the different magnetic interaction
parameters in the MC simulations also reveal the precise role of each of them
on magnetism
Evolution of shear-induced melting in dusty plasma
The spatiotemporal development of melting is studied experimentally in a 2D
dusty plasma suspension. Starting with an ordered lattice, and then suddenly
applying localized shear, a pair of counter-propagating flow regions develop. A
transition between two melting stages is observed before a steady state is
reached. Melting spreads with a front that propagates at the transverse sound
speed. Unexpectedly, coherent longitudinal waves are excited in the flow
region.Comment: 5 pages text, 3 figures, in press Physical Review Letters 2010
Filtration and transport of heavy metals in graphene oxide enabled sand columns
A fixed-bed sand column with graphene oxide (GO) layer was used to remove heavy metals (Cu(II) and Pb(II)) from an aqueous solution injected under steady flow. Due to the time constrained kinetic process of heavy metal sorption to GO, removal efficiency was affected by the injection flow rate. When injection flow rate changed from 1 to 5 mL min−1, the removal efficiency of the two metals decreased from 15.3% to 10.3% and from 26.7% to 19.0% for Cu(II) and Pb(II), respectively. Provided a fixed concentration of heavy metals in the injected flow, an increase in GO in column from 10 to 30 mg resulted in an sharp increase in the removal efficiency of Pb(II) from 26.7% to 40.5%. When Cu(II) and Pb(II) were applied simultaneously, the removal efficiency of the two metals was lower than when applied by individually. GO-sand column performance was much better for the removal of Pb(II) than for Cu(II) in each corresponding treatment. When breakthrough curve (BTC) data were simulated by the convection-dispersion-reaction (CDER) model, the fittings for Cu in every treatment were better than that of Pb in corresponding treatment. Considering the small amount of GO used to enable the sand columns that resulted in a great increase in k value, compared to the GO-free sand columns, the authors propose GO as an effective adsorption media in filters and reactive barriers to remove Pb(II) from flowing water
Local electronic structures on the superconducting interface
Motivated by the recent discovery of superconductivity on the heterointerface
, we theoretically investigate its local electronic
structures near an impurity considering the influence of Rashba-type spin-orbit
interaction (RSOI) originated in the lack of inversion symmetry. We find that
local density of states near an impurity exhibits the in-gap resonance peaks
due to the quasiparticle scattering on the Fermi surface with the reversal sign
of the pairing gap caused by the mixed singlet and RSOI-induced triplet
superconducting state. We also analyze the evolutions of density of states and
local density of states with the weight of triplet pairing component determined
by the strength of RSOI, which will be widely observed in thin films of
superconductors with surface or interface-induced RSOI, or various
noncentrosymmetric superconductors in terms of point contact tunneling and
scanning tunneling microscopy, and thus reveal an admixture of the spin singlet
and RSOI-induced triplet superconducting states.Comment: Phys. Rev. B 81, 144504 (2010)
Dynamical Monte Carlo investigation of spin reversals and nonequilibrium magnetization of single-molecule magnets
In this paper, we combine thermal effects with Landau-Zener (LZ) quantum
tunneling effects in a dynamical Monte Carlo (DMC) framework to produce
satisfactory magnetization curves of single-molecule magnet (SMM) systems. We
use the giant spin approximation for SMM spins and consider regular lattices of
SMMs with magnetic dipolar interactions (MDI). We calculate spin reversal
probabilities from thermal-activated barrier hurdling, direct LZ tunneling, and
thermal-assisted LZ tunnelings in the presence of sweeping magnetic fields. We
do systematical DMC simulations for Mn systems with various temperatures
and sweeping rates. Our simulations produce clear step structures in
low-temperature magnetization curves, and our results show that the thermally
activated barrier hurdling becomes dominating at high temperature near 3K and
the thermal-assisted tunnelings play important roles at intermediate
temperature. These are consistent with corresponding experimental results on
good Mn samples (with less disorders) in the presence of little
misalignments between the easy axis and applied magnetic fields, and therefore
our magnetization curves are satisfactory. Furthermore, our DMC results show
that the MDI, with the thermal effects, have important effects on the LZ
tunneling processes, but both the MDI and the LZ tunneling give place to the
thermal-activated barrier hurdling effect in determining the magnetization
curves when the temperature is near 3K. This DMC approach can be applicable to
other SMM systems, and could be used to study other properties of SMM systems.Comment: Phys Rev B, accepted; 10 pages, 6 figure
Periodic Modulation Effect on Self-Trapping of Two weakly coupled Bose-Einstein Condensates
With phase space analysis approach, we investigate thoroughly the
self-trapping phenomenon for two weakly coupled Bose-Einstein condensates (BEC)
in a symmetric double-well potential. We identify two kinds of self-trapping by
their different relative phase behavior. With applying a periodic modulation on
the energy bias of the system we find the occurrence of the self-trapping can
be controlled, saying, the transition parameters can be adjusted effectively by
the periodic modulation. Analytic expressions for the dependence of the
transition parameters on the modulation parameters are derived for high and low
frequency modulations. For an intermediate frequency modulation, we find the
resonance between the periodic modulation and nonlinear Rabi oscillation
dramatically affects the tunnelling dynamics and demonstrate many novel
phenomena. Finally, we study the effects of many-body quantum fluctuation on
self-trapping and discuss the possible experimental realization of the model.Comment: 7 pages, 11 figure
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