2,197 research outputs found
A Spectroscopic Study of Mass Outflows in the Interacting Binary RY Scuti
The massive interacting binary RY Scuti is an important representative of an
active mass-transferring system that is changing before our eyes and which may
be an example of the formation of a Wolf-Rayet star through tidal stripping.
Utilizing new and previously published spectra, we present examples of how a
number of illustrative absorption and emission features vary during the binary
orbit. We identify spectral features associated with each component, calculate
a new, double-lined spectroscopic binary orbit, and find masses of 7.1 +/- 1.2
M_sun for the bright supergiant and 30.0 +/- 2.1 M_sun for the hidden massive
companion. Through tomographic reconstruction of the component spectra from the
composite spectra, we confirm the O9.7 Ibpe spectral class of the bright
supergiant and discover a B0.5 I spectrum associated with the hidden massive
companion; however, we suggest that the latter is actually the spectrum of the
photosphere of the accretion torus immediately surrounding the massive
companion. We describe the complex nature of the mass loss flows from the
system in the context of recent hydrodynamical models for beta Lyr, leading us
to conclude RY Scuti has matter leaving the system in two ways: 1) a bipolar
outflow from winds generated by the hidden massive companion, and 2) mass from
the bright O9.7 Ibpe supergiant flowing from the region near the L2 point to
fill out a large, dense circumbinary disk. This circumbinary disk (radius ~ 1
AU) may feed the surrounding double-toroidal nebula (radius ~ 2000 AU).Comment: 41 pages with 7 tables and 11 figures, accepted to Ap
Ultrafast mid-infrared spectroscopy by chirped pulse upconversion in 1800-1000cm(-1) region
Broadband femtosecond mid-infrared pulses can be converted into the visible spectral region by chirped pulse upconversion. We report here the upconversion of pump probe transient signals in the frequency region below 1800c
Enhanced Fatty Acid Oxidation and FATP4 Protein Expression after Endurance Exercise Training in Human Skeletal Muscle
FATP1 and FATP4 appear to be important for the cellular uptake and handling of long chain fatty acids (LCFA). These findings were obtained from loss- or gain of function models. However, reports on FATP1 and FATP4 in human skeletal muscle are limited. Aerobic training enhances lipid oxidation; however, it is not known whether this involves up-regulation of FATP1 and FATP4 protein. Therefore, the aim of this project was to investigate FATP1 and FATP4 protein expression in the vastus lateralis muscle from healthy human individuals and to what extent FATP1 and FATP4 protein expression were affected by an increased fuel demand induced by exercise training. Eight young healthy males were recruited to the study. All subjects were non smokers and did not participate in regular physical activity (<1 time per week for the past 6 months, VO2peak 3.4±0.1 l O2 min−1). Subjects underwent an 8 week supervised aerobic training program. Training induced an increase in VO2peak from 3.4±0.1 to 3.9±0.1 l min−1 and citrate synthase activity was increased from 53.7±2.5 to 80.8±3.7 µmol g−1 min−1. The protein content of FATP4 was increased by 33%, whereas FATP1 protein content was reduced by 20%. Interestingly, at the end of the training intervention a significant association (r2 = 0.74) between the observed increase in skeletal muscle FATP4 protein expression and lipid oxidation during a 120 min endurance exercise test was observed. In conclusion, based on the present findings it is suggested that FATP1 and FATP4 proteins perform different functional roles in handling LCFA in skeletal muscle with FATP4 apparently more important as a lipid transport protein directing lipids for lipid oxidation
Phase locking the spin precession in a storage ring
This letter reports the successful use of feedback from a spin polarization
measurement to the revolution frequency of a 0.97 GeV/ bunched and polarized
deuteron beam in the Cooler Synchrotron (COSY) storage ring in order to control
both the precession rate ( kHz) and the phase of the horizontal
polarization component. Real time synchronization with a radio frequency (rf)
solenoid made possible the rotation of the polarization out of the horizontal
plane, yielding a demonstration of the feedback method to manipulate the
polarization. In particular, the rotation rate shows a sinusoidal function of
the horizontal polarization phase (relative to the rf solenoid), which was
controlled to within a one standard deviation range of rad. The
minimum possible adjustment was 3.7 mHz out of a revolution frequency of 753
kHz, which changes the precession rate by 26 mrad/s. Such a capability meets a
requirement for the use of storage rings to look for an intrinsic electric
dipole moment of charged particles
Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data
Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample
Bose-Einstein Correlations of Three Charged Pions in Hadronic Z^0 Decays
Bose-Einstein Correlations (BEC) of three identical charged pions were
studied in 4 x 10^6 hadronic Z^0 decays recorded with the OPAL detector at LEP.
The genuine three-pion correlations, corrected for the Coulomb effect, were
separated from the known two-pion correlations by a new subtraction procedure.
A significant genuine three-pion BEC enhancement near threshold was observed
having an emitter source radius of r_3 = 0.580 +/- 0.004 (stat.) +/- 0.029
(syst.) fm and a strength of \lambda_3 = 0.504 +/- 0.010 (stat.) +/- 0.041
(syst.). The Coulomb correction was found to increase the \lambda_3 value by
\~9% and to reduce r_3 by ~6%. The measured \lambda_3 corresponds to a value of
0.707 +/- 0.014 (stat.) +/- 0.078 (syst.) when one takes into account the
three-pion sample purity. A relation between the two-pion and the three-pion
source parameters is discussed.Comment: 19 pages, LaTeX, 5 eps figures included, accepted by Eur. Phys. J.
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Genome-wide association study identifies 30 loci associated with bipolar disorder.
Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder
Search for supersymmetry in events with b-quark jets and missing transverse energy in pp collisions at 7 TeV
Results are presented from a search for physics beyond the standard model
based on events with large missing transverse energy, at least three jets, and
at least one, two, or three b-quark jets. The study is performed using a sample
of proton-proton collision data collected at sqrt(s) = 7 TeV with the CMS
detector at the LHC in 2011. The integrated luminosity of the sample is 4.98
inverse femtobarns. The observed number of events is found to be consistent
with the standard model expectation, which is evaluated using control samples
in the data. The results are used to constrain cross sections for the
production of supersymmetric particles decaying to b-quark-enriched final
states in the context of simplified model spectra.Comment: Submitted to Physical Review
ALCAM (CD166) Expression and Serum Levels in Pancreatic Cancer
BACKGROUND: This study was conducted to evaluate the expression of the activated leukocyte cell adhesion molecule (ALCAM) in pancreatic cancer (PAC) and to determine whether or not the ectodomain shedding of ALCAM (s-ALCAM) could serve as a biomarker in the peripheral blood of PAC patients. MATERIAL AND METHODS: Tissue specimens and blood sera of patients with PAC (n = 264 and n = 116, respectively) and the sera of 115 patients with chronic pancreatitis (CP) were analyzed via ALCAM immunohistochemistry and s-ALCAM ELISA tests. Results were correlated with clinical, histopathological, and patient survival data (Chi-square test, Kaplan-Meier analysis, log-rank test, respectively). RESULTS: ALCAM was expressed in the majority of PAC lesions. Immunohistochemistry and serum ELISA tests revealed no association between ALCAM expression in primary tumors or s-ALCAM and clinical or histopathological data. Neither ALCAM nor s-ALCAM showed a significant impact regarding overall survival (p = 0.261 and p = 0.660, respectively). S-ALCAM serum levels were significantly elevated compared to the sera of CP patients (p<0.001). The sensitivity of s-ALCAM in detecting PAC was 58.6% at a specificity of 73.9% (AUC = 0.69). CONCLUSIONS: ALCAM is expressed in the majority of PAC lesions, but statistical analysis revealed no association with clinical or pathological data. Although significantly elevated in patients with PAC, the sensitivity and specificity of the s-ALCAM serum quantification test was low. Therefore, its potential as a novel diagnostic marker for PAC remains elusive and further investigations are required
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