2,330 research outputs found
Juniper from Ethiopia contains a large-scale precipitation signal
Most semiarid regions are facing an increasing scarcity of woody vegetation due mainly to anthropogenic deforestation aggravated by climate changes. However, there is insufficient information to reconstruct past changes in climate and to evaluate the implications of future climate changes on the vegetation. Tree-ring analysis is a powerful tool for studying tree age, population dynamics, growth behavior, and climate-growth relationships among tropical tree species and for gaining information about the environmental forces driving growth change as well as for developing proxies for climate reconstruction. Wood anatomical and dendrochronological methods were used on Juniperus procera trees from two Ethiopian highland forests to check (i) whether tree-ring series of juniper are cross-datable and hence suitable for building tree-ring chronologies, and if so, (ii) which climate factors mainly drive wood formation in juniper from this region. Visible growth layers of the juniper wood were shown to be annual rings. Tree-ring sequences could be cross-dated between trees growing at the same site and between trees growing at sites 350 km apart. Evidence was found that annual growth of junipers is mainly controlled by one climatic factor, precipitation. This strong precipitation influence proves the potential of African juniper chronologies for accurate climate reconstruction and points out the relevance of building a network of juniper chronologies across East Africa
Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI
Purpose: This prospective clinical study assesses the feasibility of training
a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model
fitting to diffusion-weighted magnetic resonance imaging (DW-MRI) data and
evaluates its performance. Methods: In May 2011, ten male volunteers (age
range: 29 to 53 years, mean: 37 years) underwent DW-MRI of the upper abdomen on
1.5T and 3.0T magnetic resonance scanners. Regions of interest in the left and
right liver lobe, pancreas, spleen, renal cortex, and renal medulla were
delineated independently by two readers. DNNs were trained for IVIM model
fitting using these data; results were compared to least-squares and Bayesian
approaches to IVIM fitting. Intraclass Correlation Coefficients (ICC) were used
to assess consistency of measurements between readers. Intersubject variability
was evaluated using Coefficients of Variation (CV). The fitting error was
calculated based on simulated data and the average fitting time of each method
was recorded. Results: DNNs were trained successfully for IVIM parameter
estimation. This approach was associated with high consistency between the two
readers (ICCs between 50 and 97%), low intersubject variability of estimated
parameter values (CVs between 9.2 and 28.4), and the lowest error when compared
with least-squares and Bayesian approaches. Fitting by DNNs was several orders
of magnitude quicker than the other methods but the networks may need to be
re-trained for different acquisition protocols or imaged anatomical regions.
Conclusion: DNNs are recommended for accurate and robust IVIM model fitting to
DW-MRI data. Suitable software is available at (1)
Septic Arthritis Caused by Legionella dumoffii in a Patient with Systemic Lupus Erythematosus-Like Disease
We describe a patient with systemic lupus erythematosus (SLE)-like disease on immunosuppressive treatment who developed septic arthritis of the knee involving Legionella dumoffii. Cultures initially remained negative. A broad-range 16S PCR using synovial fluid revealed L. dumoffii rRNA genes, a finding that was subsequently confirmed by positive Legionella culture results
Efficient estimation in the semiparametric normal regression-copula model with a focus on QTL mapping
The semiparametric normal copula model is studied with a correlation matrix that depends on a covariate. The bivariate version of this regression-copula model has been proposed for statistical analysis of Quantitative Trait Loci (QTL) via twin data. Appropriate linear combinations of Van der Waerden’s normal scores rank correlation coefficients yield -consistent estimators of the coefficients in the correlation function, i.e. of the regression parameters. They are used to construct semiparametrically efficient estimators of the regression parameters
Inelastic collision processes in ozone and their relation to atmospheric pressure broadening
The research task employs infrared double-resonance to determine rotational energy transfer rates and pathways, in both the ground and vibrationally excited states of ozone. The resulting data base will then be employed to test inelastic scattering theories and to assess intermolecular potential models, both of which are necessary for the systematization and prediction of infrared pressure-broadening coefficients, which are in turn required by atmospheric ozone monitoring techniques based on infrared remote sensing. In addition, observation of excited-state absorption transitions will permit us to improve the determination of the 2 nu(sub 3), nu(sub 1) + nu(sub 2), and 2 nu(sub 1) rotational constants and to derive band strengths for hot-band transitions involving these levels
ALMA CO J=6-5 observations of IRAS16293-2422: Shocks and entrainment
Observations of higher-excited transitions of abundant molecules such as CO
are important for determining where energy in the form of shocks is fed back
into the parental envelope of forming stars. The nearby prototypical and
protobinary low-mass hot core, IRAS16293-2422 (I16293) is ideal for such a
study. The source was targeted with ALMA for science verification purposes in
band 9, which includes CO J=6-5 (E_up/k_B ~ 116 K), at an unprecedented spatial
resolution (~0.2", 25 AU). I16293 itself is composed of two sources, A and B,
with a projected distance of 5". CO J=6-5 emission is detected throughout the
region, particularly in small, arcsecond-sized hotspots, where the outflow
interacts with the envelope. The observations only recover a fraction of the
emission in the line wings when compared to data from single-dish telescopes,
with a higher fraction of emission recovered at higher velocities. The very
high angular resolution of these new data reveal that a bow shock from source A
coincides, in the plane of the sky, with the position of source B. Source B, on
the other hand, does not show current outflow activity. In this region, outflow
entrainment takes place over large spatial scales, >~ 100 AU, and in small
discrete knots. This unique dataset shows that the combination of a
high-temperature tracer (e.g., CO J=6-5) and very high angular resolution
observations is crucial for interpreting the structure of the warm inner
environment of low-mass protostars.Comment: Accepted for publication in A&A Letter
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