Systematic Theoretical Search for Dibaryons in a Relativistic Model

A relativistic quark potential model is used to do a systematic search for quasi-stable dibaryon states in the $u$, $d$, and $s$ three flavor world. Flavor symmetry breaking and channel coupling effects are included and an adiabatic method and fractional parentage expansion technique are used in the calculations. The relativistic model predicts dibaryon candidates completely consistent with the nonrelativistic model.Comment: 12 pages, latex, no figure

Effective Baryon-Baryon Potentials in the Quark Delocalization and Color Screening Model

The quark delocalization and color screening model is used for a systematic study of the effective potential between baryons in the u,d and s sector. The model is constrained by the properties of baryons and N-N scattering. The effective potentials for the N-N (IJ=01,10,11,00) channels and the N-Lambda and N-Sigma (IJ = (1/2)1, (1/2)0, (3/2)1, (3/2)0) channels fit the N-N, N-Lambda and N-Sigma scattering data reasonably well. This model predicts: There are rather strong effective attractions between decuplet-baryons; the effective attractions between octet-baryons are weak or even repulsive; and the attractions between decuplet- and octet-baryons lie in between.Comment: 12 pp. RevTeX + 8 figs.ps, submitted to Nucl. Phys.

Quark Delocalization, Color Screening Model and Nucleon-Baryon Scattering

We apply the quark delocalization and color screening model to nucleon-baryon scattering. A semi-quantitative fit to N-N, N-Lambda and N-Sigma phase shifts and scattering cross sections is obtained without invoking meson exchange. Quarks delocalize reasonably in all of the different flavor channels to induce effective nucleon-baryon interactions with both a repulsive core and with an intermediate range attraction in the cases expected.Comment: 14 pp. RevTeX plus 13 figs.ps, submitted to Phys. Rev.

TMRT observations of 26 pulsars at 8.6 GHz

Integrated pulse profiles at 8.6~GHz obtained with the Shanghai Tian Ma Radio Telescope (TMRT) are presented for a sample of 26 pulsars. Mean flux densities and pulse width parameters of these pulsars are estimated. For eleven pulsars these are the first high-frequency observations and for a further four, our observations have a better signal-to-noise ratio than previous observations. For one (PSR J0742-2822) the 8.6~GHz profiles differs from previously observed profiles. A comparison of 19 profiles with those at other frequencies shows that in nine cases the separation between the outmost leading and trailing components decreases with frequency, roughly in agreement with radius-to-frequency mapping, whereas in the other ten the separation is nearly constant. Different spectral indices of profile components lead to the variation of integrated pulse profile shapes with frequency. In seven pulsars with multi-component profiles, the spectral indices of the central components are steeper than those of the outer components. For the 12 pulsars with multi-component profiles in the high-frequency sample, we estimate the core width using gaussian fitting and discuss the width-period relationship.Comment: 33 pages, 49 figures, 5 Tables; accepted by Ap

Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation

This paper addresses text-supervised semantic segmentation, aiming to learn a model capable of segmenting arbitrary visual concepts within images by using only image-text pairs without dense annotations. Existing methods have demonstrated that contrastive learning on image-text pairs effectively aligns visual segments with the meanings of texts. We notice that there is a discrepancy between text alignment and semantic segmentation: A text often consists of multiple semantic concepts, whereas semantic segmentation strives to create semantically homogeneous segments. To address this issue, we propose a novel framework, Image-Text Co-Decomposition (CoDe), where the paired image and text are jointly decomposed into a set of image regions and a set of word segments, respectively, and contrastive learning is developed to enforce region-word alignment. To work with a vision-language model, we present a prompt learning mechanism that derives an extra representation to highlight an image segment or a word segment of interest, with which more effective features can be extracted from that segment. Comprehensive experimental results demonstrate that our method performs favorably against existing text-supervised semantic segmentation methods on six benchmark datasets.Comment: CVPR 202

SDSS J013127.34−-032100.1: A newly discovered radio-loud quasar at z=5.18z=5.18 with extremely high luminosity

Only very few z>5 quasars discovered to date are radio-loud, with a radio-to-optical flux ratio (radio-loudness parameter) higher than 10. Here we report the discovery of an optically luminous radio-loud quasar, SDSS J013127.34-032100.1 (J0131-0321 in short), at z=5.18+-0.01 using the Lijiang 2.4m and Magellan telescopes. J0131-0321 has a spectral energy distribution consistent with that of radio-loud quasars. With an i-band magnitude of 18.47 and radio flux density of 33 mJy, its radio-loudness parameter is ~100. The optical and near-infrared spectra taken by Magellan enable us to estimate its bolometric luminosity to be L_bol ~ 1.1E48 erg/s, approximately 4.5 times greater than that of the most distant quasar known to date. The black hole mass of J0131-0321 is estimated to be 2.7E9 solar masses, with an uncertainty up to 0.4 dex. Detailed physical properties of this high-redshift, radio-loud, potentially super-Eddington quasar can be probed in the future with more dedicated and intensive follow-up observations using multi-wavelength facilities.Comment: 5 pages, 3 figures, accepted to ApJ

Innate resistance to Leishmania amazonensis Infection in rat is dependent on NOS2

Leishmania infection causes diverse clinical manifestations in humans. The disease outcome is complicated by the combination of many host and parasite factors. Inbred mouse strains vary in resistance to Leishmania major but are highly susceptible to Leishmania amazonensis infection. However, rats are highly resistant to L. amazonensis infection due to unknown mechanisms. We use the inducible nitric oxide synthase (Nos2) gene knockout rat model (Nos2−/− rat) to investigate the role of NOS2 against leishmania infection in rats. Our results demonstrated that diversion toward the NOS2 pathway is the key factor explaining the resistance of rats against L. amazonensis infection. Rats deficient in NOS2 are susceptible to L. amazonensis infection even though their immune response to infection is still strong. Moreover, adoptive transfer of NOS2 competent macrophages into Nos2−/− rats significantly reduced disease development and parasite load. Thus, we conclude that the distinct L-arginine metabolism, observed in rat macrophages, is the basis of the strong innate resistance to Leishmania. These data highlight that macrophages from different hosts possess distinctive properties and produce different outcomes in innate immunity to Leishmania infections

Use of Bayesian networks to dissect the complexity of genetic disease: application to the Genetic Analysis Workshop 17 simulated data

Complex diseases are often the downstream event of a number of risk factors, including both environmental and genetic variables. To better understand the mechanism of disease onset, it is of great interest to systematically investigate the crosstalk among various risk factors. Bayesian networks provide an intuitive graphical interface that captures not only the association but also the conditional independence and dependence structures among the variables, resulting in sparser relationships between risk factors and the disease phenotype than traditional correlation-based methods. In this paper, we apply a Bayesian network to dissect the complex regulatory relationships among disease traits and various risk factors for the Genetic Analysis Workshop 17 simulated data. We use the Bayesian network as a tool for the risk prediction of disease outcome