2,021 research outputs found
Scaling law in target-hunting processes
We study the hunting process for a target, in which the hunter tracks the
goal by smelling odors it emits. The odor intensity is supposed to decrease
with the distance it diffuses. The Monte Carlo experiment is carried out on a
2-dimensional square lattice. Having no idea of the location of the target, the
hunter determines its moves only by random attempts in each direction. By
sorting the searching time in each simulation and introducing a variable to
reflect the sequence of searching time, we obtain a curve with a wide plateau,
indicating a most probable time of successfully finding out the target. The
simulations reveal a scaling law for the searching time versus the distance to
the position of the target. The scaling exponent depends on the sensitivity of
the hunter. Our model may be a prototype in studying such the searching
processes as various foods-foraging behavior of the wild animals.Comment: 7 figure
Anomalous escape governed by thermal 1/f noise
We present an analytic study for subdiffusive escape of overdamped particles
out of a cusp-shaped parabolic potential well which are driven by thermal,
fractional Gaussian noise with a power spectrum. This
long-standing challenge becomes mathematically tractable by use of a
generalized Langevin dynamics via its corresponding non-Markovian,
time-convolutionless master equation: We find that the escape is governed
asymptotically by a power law whose exponent depends exponentially on the ratio
of barrier height and temperature. This result is in distinct contrast to a
description with a corresponding subdiffusive fractional Fokker-Planck
approach; thus providing experimentalists an amenable testbed to differentiate
between the two escape scenarios
In-orbit Vignetting Calibrations of XMM-Newton Telescopes
We describe measurements of the mirror vignetting in the XMM-Newton
Observatory made in-orbit, using observations of SNR G21.5-09 and SNR
3C58 with the EPIC imaging cameras. The instrument features that complicate
these measurements are briefly described. We show the spatial and energy
dependences of measured vignetting, outlining assumptions made in deriving the
eventual agreement between simulation and measurement. Alternate methods to
confirm these are described, including an assessment of source elongation with
off-axis angle, the surface brightness distribution of the diffuse X-ray
background, and the consistency of Coma cluster emission at different position
angles. A synthesis of these measurements leads to a change in the XMM
calibration data base, for the optical axis of two of the three telescopes, by
in excess of 1 arcminute. This has a small but measureable effect on the
assumed spectral responses of the cameras for on-axis targets.Comment: Accepted by Experimental Astronomy. 26 pages, 18 figure
Use of soil moisture information in yield models
There are no author-identified significant results in this report
Unusual Response to a Localized Perturbation in a Generalized Elastic Model
The generalized elastic model encompasses several physical systems such as
polymers, membranes, single file systems, fluctuating surfaces and rough
interfaces. We consider the case of an applied localized potential, namely an
external force acting only on a single (tagged) probe, leaving the rest of the
system unaffected. We derive the fractional Langevin equation for the tagged
probe, as well as for a generic (untagged) probe, where the force is not
directly applied. Within the framework of the fluctuation-dissipation
relations, we discuss the unexpected physical scenarios arising when the force
is constant and time periodic, whether or not the hydrodynamic interactions are
included in the model. For short times, in case of the constant force, we show
that the average drift is linear in time for long range hydrodynamic
interactions and behaves ballistically or exponentially for local hydrodynamic
interactions. Moreover, it can be opposite to the direction of external
disturbance for some values of the model's parameters. When the force is time
periodic, the effects are macroscopic: the system splits into two distinct
spatial regions whose size is proportional to the value of the applied
frequency. These two regions are characterized by different amplitudes and
phase shifts in the response dynamics
Discovery of superstrong, fading, iron line emission and double-peaked Balmer lines of the galaxy SDSSJ0952+2143 - the light echo of a huge flare
We report the discovery of superstrong, fading, high-ionization iron line
emission in the galaxy SDSSJ095209.56+214313.3 (SDSSJ0952+2143 hereafter),
which must have been caused by an X-ray outburst of large amplitude.
SDSSJ0952+2143 is unique in its strong multiwavelength variability; such a
broadband emission-line and continuum response has not been observed before.
The strong iron line emission is accompanied by unusual Balmer line emission
with a broad base, narrow core and double-peaked narrow horns, and strong HeII
emission. These lines, while strong in the SDSS spectrum taken in 2005, have
faded away significantly in new spectra taken in December 2007. Comparison of
SDSS, 2MASS, GALEX and follow-up GROND photometry reveals variability in the
NUV, optical and NIR band. Taken together, these unusual observations can be
explained by a giant outburst in the EUV--X-ray band, detected even in the
optical and NIR. The intense and variable iron, Helium and Balmer lines
represent the ``light echo'' of the flare, as it traveled through circumnuclear
material. The outburst may have been caused by the tidal disruption of a star
by a supermassive black hole. Spectroscopic surveys such as SDSS are well
suited to detect emission-line light echoes of such rare flare events.
Reverberation-mapping of these light echoes can then be used as a new and
efficient probe of the physical conditions in the circumnuclear material in
non-active or active galaxies.Comment: ApJ Letters, 678, L13 (May 1 issue); incl. 4 colour figures. This and
related papers on tidal disruption flares also available at
http://www.xray.mpe.mpg.de/~skomossa
MetabR: an R script for linear model analysis of quantitative metabolomic data
Background
Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings
Here we present a simple menu-driven program, âMetabRâ, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions
We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org
MetabR: an R script for linear model analysis of quantitative metabolomic data
Background
Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings
Here we present a simple menu-driven program, âMetabRâ, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions
We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/ webcite
Dynamic regulation of adipose tissue metabolism in the domestic broiler chicken â an alternative model for studies of human obesity
Background
The domestic chicken is an attractive, but underutilized, animal model for studies of adipose tissue biology, metabolism and obesity: 1.) like humans, chickens rely on liver rather than adipose tissue for the majority of de novo lipogenesis; 2.) quantitative trait loci (QTLs) linked to fatness in chickens contain genes implicated in human susceptibility to obesity and diabetes; 3.) chickens are naturally hyperglycemic and insulin resistant; and 4.) a broad selection of genetic models exhibiting a range of fatness are available. To date, however, little is known about regulation of adipose metabolism in this model organism.
Materials and methods
Affymetrix arrays were used to profile gene expression in abdominal adipose tissue from broiler chickens fed ad libitum or fasted for five hours and from three distinct genetic lines with low (Fayoumi and Leghorn) or high (broiler) levels of adiposity. QPCR was used to validate microarray results for select genes. Western blotting was used to assay levels of signaling proteins. Tissue levels of beta-hydroxybutyrate were measured as an index of fatty acid oxidation using a colorimetric assay. Multiple testing was controlled using q-value. Mixed linear model and multivariate clustering analysis were implemented in SAS. The Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (http://david.abcc.ncifcrf.gov/ webcite) was used for Gene Ontology (GO) and KEGG pathway enrichment analyses.
Results
A total of 1780 genes were differentially expressed in fasted vs. ad libitum fed (p\u3c0.05) tissue after correction for multiple testing. Gene Ontology and pathway analyses, combined with Western blot validation, indicated significant effects on a broad selection of pathways related to metabolism, stress signaling and adipogenesis. In particular, fasting upregulated rate-limiting genes in both the mitochondrial and peroxisomal pathways of beta-oxidation. Enhanced fatty acid oxidation in white adipose tissue was further suggested by a significant increase in tissue content of the ketone beta-hydroxybutyrate. Expression profiles suggested that, despite the relatively brief duration of feed withdrawal, fasting suppressed adipogenesis; expression of key genes in multiple steps of adipogenesis, including lineage commitment from mesenchymal stem cells, were significantly down-regulated in fasted vs. fed adipose tissue. Interestingly, fasting increased expression of several inflammatory adipokines and components of the toll-like receptor 4 signaling pathway. Microarray analysis of Fayoumi, Leghorn and broiler adipose tissue revealed that genetic leanness shared molecular signatures with the effects of fasting. In supervised clustering analysis, fasted broiler chickens clustered with lean Fayoumi and Leghorn lines rather than with the fed broiler group, suggesting that fasting manipulated expression profiles to resemble those of the lean phenotype.
Conclusions
Collectively, these data suggest that leanness in chickens is associated with increased fat utilization which, given the similarities between avian and human adipose tissue with regard to lipid metabolism, may have relevance for humans. The paradoxical increase in some inflammatory markers with an acute fast suggests that the dynamic relationship between inflammation and adipose metabolism may differ from what is observed in obesity. These results highlight chicken as a useful model in which to study the interrelationships between food intake, adipose development, metabolism, and cell stress
- âŠ