15 research outputs found
Nucleon mean free path in nuclear matter based on nuclear Schwinger-Dyson formalism
A mean free path of nucleon moving through nuclear matter with kinetic energy
of more than 100MeV is formulated based on the bare vertex nuclear
Schwinger-Dyson (BNSD) method in the Walecka model. The self-energy which is
derived from the higher order diagrams more than the forth order includes the
Feynman part of propagator of energetic nucleon and grows up rapidly as an
increase of kinetic energy. To avoid too large growth of these diagrams, meson
propagators are modified by introducing some form factors to take account of a
internal structure of hadron. It is confirmed that the mean free path
calculated by the BNSD method agrees good with experimental data if a
reasonable form factor is chosen, i.e., a dipole (quadrupole) type of form
factor with a cut-off parameter about 750 MeV 1000 MeV (1200 MeV
1500 MeV)
Vacuum Effects and Compressional Properties of Nuclear Matter in Cutoff Field Theory
Including the vacuum effects, the compressional properties of nuclear matter
are studied in the cutoff field theory. Under the Hartree approximation, the
low-energy effective Lagrangian is derived in the framework of the
renormalization group methods. The coefficients are determined in a way where
the physical results hardly depend on the value of the cutoff which is
conveniently introduced into the theory. It is shown that, to reproduce the
empirical data of the nucleus incompressibility, the compressibility of the
nuclear matter is favorable to be 250350MeV.Comment: PACS numbers, 21.65.+
Loss of maternal annexin A5 increases the likelihood of placental platelet thrombosis and foetal loss
Antiphospholipid syndrome is associated with an increased risk of thrombosis and pregnancy loss. Annexin A5 (Anxa5) is a candidate autoantigen. It is not known, however, whether endogenous Anxa5 prevents foetal loss during normal pregnancy. We found significant reductions in litter size and foetal weight in Anxa5-null mice (Anxa5-KO). These changes occurred even when only the mother was Anxa5-KO. A small amount of placental fibrin deposition was observed in the decidual tissues, but did not noticeably differ between wild-type and Anxa5-KO mice. However, immunoreactivity for integrin beta 3/CD61, a platelet marker, was demonstrated within thrombi in the arterial canals only in Anxa5-KO mothers. Subcutaneous administration of the anticoagulant heparin to pregnant Anxa5-KO mice significantly reduced pregnancy loss, suggesting that maternal Anxa5 is crucial for maintaining intact placental circulation. Hence, the presence of maternal Anxa5 minimises the risk of thrombosis in the placental circulation and reduces the risk of foetal loss
Quark condensate in nuclear matter based on Nuclear Schwinger-Dyson formalism
The effects of higher order corrections of ring diagrams for the quark
condensate are studied by using the bare vertex Nuclear Schwinger Dyson
formalism based on - model. At the high density the quark
condensate is reduced by the higher order contribution of ring diagrams more
than the mean field theory or the Hartree-Fock
Gonadotropin-releasing hormone is prerequisite for the constitutive expression of pituitary annexin A5
Semantic role labeling using support vector machines
In this paper, we describe our systems for the CoNLL-2005 shared task. The aim of the task is semantic role labeling using a machine-learning algorithm. We apply the Support Vector Machines to the task. We added new features based on full parses and manually categorized words. We also report on system performance and what effect the newly added features had.
Augmentation of Metastin/Kisspeptin mRNA Expression by the Proestrous Luteinizing Hormone Surge in Granulosa Cells of Rats: Implications for Luteinization1
Evaluation of One Meson Loop Corrections for Nuclear Matter by Nuclear Schwinger-Dyson Equations with Bare Vertex Approximation
Percentage of n-grams of gene/protein names in test data for evaluation and TP, FP, and FN datasets
<p><b>Copyright information:</b></p><p>Taken from "Gene/protein name recognition based on support vector machine using dictionary as features"</p><p></p><p>BMC Bioinformatics 2005;6(Suppl 1):S8-S8.</p><p>Published online 24 May 2005</p><p>PMCID:PMC1869022.</p><p></p