1,843 research outputs found
A multi-treatment experimental system to examine photosynthetic differentiation in the maize leaf
BACKGROUND: The establishment of C(4 )photosynthesis in maize is associated with differential accumulation of gene transcripts and proteins between bundle sheath and mesophyll photosynthetic cell types. We have physically separated photosynthetic cell types in the leaf blade to characterize differences in gene expression by microarray analysis. Additional control treatments were used to account for transcriptional changes induced by cell preparation treatments. To analyse these data, we have developed a statistical model to compare gene expression values derived from multiple, partially confounded, treatment groups. RESULTS: Differential gene expression in the leaves of wild-type maize seedlings was characterized using the latest release of a maize long-oligonucleotide microarray produced by the Maize Array Project consortium. The complete data set is available through the project web site. Data is also available at the NCBI GEO website, series record GSE3890. Data was analysed with and without consideration of cell preparation associated stress. CONCLUSION: Empirical comparison of the two analyses suggested that consideration of stress helped to reduce the false identification of stress responsive transcripts as cell-type enriched. Using our model including a stress term, we identified 8% of features as differentially expressed between bundle sheath and mesophyll cell types under control of false discovery rate of 5%. An estimate of the overall proportion of differentially accumulating transcripts (1-π(0)) suggested that as many as 18% of the genes may be differentially expressed between B and M. The analytical model presented here is generally applicable to gene expression data and demonstrates the use of statistical elimination of confounding effects such as stress in the context of microarray analysis. We discuss the implications of the high degree of differential transcript accumulation observed with regard to both the establishment and engineering of the C(4 )syndrome
Dynamical Autler-Townes control of a phase qubit
Routers, switches, and repeaters are essential components of modern
information-processing systems. Similar devices will be needed in future
superconducting quantum computers. In this work we investigate experimentally
the time evolution of Autler-Townes splitting in a superconducting phase qubit
under the application of a control tone resonantly coupled to the second
transition. A three-level model that includes independently determined
parameters for relaxation and dephasing gives excellent agreement with the
experiment. The results demonstrate that the qubit can be used as a ON/OFF
switch with 100 ns operating time-scale for the reflection/transmission of
photons coming from an applied probe microwave tone. The ON state is realized
when the control tone is sufficiently strong to generate an Autler-Townes
doublet, suppressing the absorption of the probe tone photons and resulting in
a maximum of transmission.Comment: 8 pages, 8 figure
Efficient coupling of photons to a single molecule and the observation of its resonance fluorescence
Single dye molecules at cryogenic temperatures display many spectroscopic
phenomena known from free atoms and are thus promising candidates for
fundamental quantum optical studies. However, the existing techniques for the
detection of single molecules have either sacrificed the information on the
coherence of the excited state or have been inefficient. Here we show that
these problems can be addressed by focusing the excitation light near to the
absorption cross section of a molecule. Our detection scheme allows us to
explore resonance fluorescence over 9 orders of magnitude of excitation
intensity and to separate its coherent and incoherent parts. In the strong
excitation regime, we demonstrate the first observation of the Mollow triplet
from a single solid-state emitter. Under weak excitation we report the
detection of a single molecule with an incident power as faint as 150 attoWatt,
paving the way for studying nonlinear effects with only a few photons.Comment: 6 figure
Graphene plasmonics
Two rich and vibrant fields of investigation, graphene physics and
plasmonics, strongly overlap. Not only does graphene possess intrinsic plasmons
that are tunable and adjustable, but a combination of graphene with noble-metal
nanostructures promises a variety of exciting applications for conventional
plasmonics. The versatility of graphene means that graphene-based plasmonics
may enable the manufacture of novel optical devices working in different
frequency ranges, from terahertz to the visible, with extremely high speed, low
driving voltage, low power consumption and compact sizes. Here we review the
field emerging at the intersection of graphene physics and plasmonics.Comment: Review article; 12 pages, 6 figures, 99 references (final version
available only at publisher's web site
Presenting the Uncertainties of Odds Ratios Using Empirical-Bayes Prediction Intervals
Quantifying exposure-disease associations is a central issue in epidemiology. Researchers of a study often present an odds ratio (or a logarithm of odds ratio, logOR) estimate together with its confidence interval (CI), for each exposure they examined. Here the authors advocate using the empirical-Bayes-based ‘prediction intervals’ (PIs) to bound the uncertainty of logORs. The PI approach is applicable to a panel of factors believed to be exchangeable (no extra information, other than the data itself, is available to distinguish some logORs from the others). The authors demonstrate its use in a genetic epidemiological study on age-related macular degeneration (AMD). The proposed PIs can enjoy straightforward probabilistic interpretations—a 95% PI has a probability of 0.95 to encompass the true value, and the expected number of true values that are being encompassed is for a total of 95% PIs. The PI approach is theoretically more efficient (producing shorter intervals) than the traditional CI approach. In the AMD data, the average efficiency gain is 51.2%. The PI approach is advocated to present the uncertainties of many logORs in a study, for its straightforward probabilistic interpretations and higher efficiency while maintaining the nominal coverage probability
A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation
Nanoparticles introduced in living cells are capable of strongly promoting
the aggregation of peptides and proteins. We use here molecular dynamics
simulations to characterise in detail the process by which nanoparticle
surfaces catalyse the self- assembly of peptides into fibrillar structures. The
simulation of a system of hundreds of peptides over the millisecond timescale
enables us to show that the mechanism of aggregation involves a first phase in
which small structurally disordered oligomers assemble onto the nanoparticle
and a second phase in which they evolve into highly ordered beta-sheets as
their size increases
A frequentist framework of inductive reasoning
Reacting against the limitation of statistics to decision procedures, R. A.
Fisher proposed for inductive reasoning the use of the fiducial distribution, a
parameter-space distribution of epistemological probability transferred
directly from limiting relative frequencies rather than computed according to
the Bayes update rule. The proposal is developed as follows using the
confidence measure of a scalar parameter of interest. (With the restriction to
one-dimensional parameter space, a confidence measure is essentially a fiducial
probability distribution free of complications involving ancillary statistics.)
A betting game establishes a sense in which confidence measures are the only
reliable inferential probability distributions. The equality between the
probabilities encoded in a confidence measure and the coverage rates of the
corresponding confidence intervals ensures that the measure's rule for
assigning confidence levels to hypotheses is uniquely minimax in the game.
Although a confidence measure can be computed without any prior distribution,
previous knowledge can be incorporated into confidence-based reasoning. To
adjust a p-value or confidence interval for prior information, the confidence
measure from the observed data can be combined with one or more independent
confidence measures representing previous agent opinion. (The former confidence
measure may correspond to a posterior distribution with frequentist matching of
coverage probabilities.) The representation of subjective knowledge in terms of
confidence measures rather than prior probability distributions preserves
approximate frequentist validity.Comment: major revisio
Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm
Over the past five decades, k-means has become the clustering algorithm of
choice in many application domains primarily due to its simplicity, time/space
efficiency, and invariance to the ordering of the data points. Unfortunately,
the algorithm's sensitivity to the initial selection of the cluster centers
remains to be its most serious drawback. Numerous initialization methods have
been proposed to address this drawback. Many of these methods, however, have
time complexity superlinear in the number of data points, which makes them
impractical for large data sets. On the other hand, linear methods are often
random and/or sensitive to the ordering of the data points. These methods are
generally unreliable in that the quality of their results is unpredictable.
Therefore, it is common practice to perform multiple runs of such methods and
take the output of the run that produces the best results. Such a practice,
however, greatly increases the computational requirements of the otherwise
highly efficient k-means algorithm. In this chapter, we investigate the
empirical performance of six linear, deterministic (non-random), and
order-invariant k-means initialization methods on a large and diverse
collection of data sets from the UCI Machine Learning Repository. The results
demonstrate that two relatively unknown hierarchical initialization methods due
to Su and Dy outperform the remaining four methods with respect to two
objective effectiveness criteria. In addition, a recent method due to Erisoglu
et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms
(Springer, 2014). arXiv admin note: substantial text overlap with
arXiv:1304.7465, arXiv:1209.196
Isotocin controls ion regulation through regulating ionocyte progenitor differentiation and proliferation
The present study using zebrafish as a model explores the role of isotocin, a homolog of oxytocin, in controlling ion regulatory mechanisms. Double-deionized water treatment for 24 h significantly stimulated isotocin mRNA expression in zebrafish embryos. Whole-body Cl−, Ca2+, and Na+ contents, mRNA expressions of ion transporters and ionocyte-differentiation related transcription factors, and the number of skin ionocytes decreased in isotocin morphants. In contrast, overexpression of isotocin caused an increase in ionocyte numbers. Isotocin morpholino caused significant suppression of foxi3a mRNA expression, while isotocin cRNA stimulated foxi3a mRNA expressions at the tail-bud stage of zebrafish embryos. The density of P63 (an epidermal stem cell marker)-positive cells was downregulated by isotocin morpholinos and was upregulated by isotocin cRNA. Taken together, isotocin stimulates the proliferation of epidermal stem cells and differentiation of ionocyte progenitors by regulating the P63 and Foxi3a transcription factors, consequently enhancing the functional activities of ionocytes
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Observational constraints on atmospheric and oceanic cross-equatorial heat transports: revisiting the precipitation asymmetry problem in climate models
Satellite based top-of-atmosphere (TOA) and surface radiation budget observations are combined with mass corrected vertically integrated atmospheric energy divergence and tendency from reanalysis to infer the regional distribution of the TOA, atmospheric and surface energy budget terms over the globe. Hemispheric contrasts in the energy budget terms are used to determine the radiative and combined sensible and latent heat contributions to the cross-equatorial heat transports in the atmosphere (AHT_EQ) and ocean (OHT_EQ). The contrast in net atmospheric radiation implies an AHT_EQ from the northern hemisphere (NH) to the southern hemisphere (SH) (0.75 PW), while the hemispheric difference in sensible and latent heat implies an AHT_EQ in the opposite direction (0.51 PW), resulting in a net NH to SH AHT_EQ (0.24 PW). At the surface, the hemispheric contrast in the radiative component (0.95 PW) dominates, implying a 0.44 PW SH to NH OHT_EQ. Coupled model intercomparison project phase 5 (CMIP5) models with excessive net downward surface radiation and surface-to-atmosphere sensible and latent heat transport in the SH relative to the NH exhibit anomalous northward AHT_EQ and overestimate SH tropical precipitation. The hemispheric bias in net surface radiative flux is due to too much longwave surface radiative cooling in the NH tropics in both clear and all-sky conditions and excessive shortwave surface radiation in the SH subtropics and extratropics due to an underestimation in reflection by clouds
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