Very-High-Energy Gamma-Ray Signal from Nuclear Photodisintegration as a Probe of Extragalactic Sources of Ultrahigh-Energy Nuclei

It is crucial to identify the ultrahigh-energy cosmic-ray (UHECR) sources and probe their unknown properties. Recent results from the Pierre Auger Observatory favor a heavy nuclear composition for the UHECRs. Under the requirement that heavy nuclei survive in these sources, using gamma-ray bursts as an example, we predict a diagnostic gamma-ray signal, unique to nuclei - the emission of de-excitation gamma rays following photodisintegration. These gamma rays, boosted from MeV to TeV-PeV energies, may be detectable by gamma-ray telescopes such as VERITAS, HESS, and MAGIC, and especially the next-generation CTA and AGIS. They are a promising messenger to identify and study individual UHE nuclei accelerators.Comment: 7 pages, 4 figures, accepted for publication in PRD, with extended descriptions. Conclusions unchange

Collapsing transition of spherical tethered surfaces with many holes

We investigate a tethered (i.e. fixed connectivity) surface model on spherical surfaces with many holes by using the canonical Monte Carlo simulations. Our result in this paper reveals that the model has only a collapsing transition at finite bending rigidity, where no surface fluctuation transition can be seen. The first-order collapsing transition separates the smooth phase from the collapsed phase. Both smooth and collapsed phases are characterized by Hausdorff dimension H\simeq 2, consequently, the surface becomes smooth in both phases. The difference between these two phases can be seen only in the size of surface. This is consistent with the fact that we can see no surface fluctuation transition at the collapsing transition point. These two types of transitions are well known to occur at the same transition point in the conventional surface models defined on the fixed connectivity surfaces without holes.Comment: 7 pages with 11 figure

Effect of FK 506 on spontaneous diabetes in BB rats

From days 30-120 after birth, 59 BB rats were treated with water (n = 20) or FK 506 in intragastric doses of 1 mg·kg-1·day-1 (n = 19) or 2 mg·kg-1·day-1 (n = 20). Diabetes developed in 75, 15, and 0% of the 3 groups, respectively. Animals protected from diabetes by FK 506 had normal intraperitoneal glucose tolerance tests, virtual absence histopathologically of autoimmune insulitis, and normal pancreatic insulin content. Forty-five to 75 days after stopping FK 506, ∼75% of the rats that were diabetes free at 120 days remained so

FK 506 prevents spontaneous diabetes in the BB rat.

The BB rat is the experimental analogue of human juvenile diabetes mellitus. From 30 through 120 days after birth, 59 BB rats were treated with water (n = 20), or FK 506 in daily intragastric doses of 1 mg/kg (n = 19) or 2 mg/kg (n = 20). Diabetes developed in 75%, 15%, and 0% of the three groups. Animals protected from diabetes by FK 506, and killed in the nondiabetic state at 120 days had normal intraperitoneal glucose tolerance tests, virtual absence histopathologically of autoimmune insulitis, normal pancreatic insulin content, and immunocytochemical confirmation of islet insulin and glucagon content. Forty five to 75 days after stopping FK 506, about 3/4 of the animals who were diabetes free at 120 days have remained so. These results provide support for a clinical trial of FK 506 for recent onset diabetes

Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations

Semantic segmentation is an interesting task for many deep learning researchers for scene understanding. However, recognizing details about objects' attributes can be more informative and also helpful for a better scene understanding in intelligent vehicle use cases. This paper introduces a method for simultaneous semantic segmentation and pedestrian attributes recognition. A modified dataset built on top of the Cityscapes dataset is created by adding attribute classes corresponding to pedestrian orientation attributes. The proposed method extends the SegNet model and is trained by using both the original and the attribute-enriched datasets. Based on an experiment, the proposed attribute-aware semantic segmentation approach shows the ability to slightly improve the performance on the Cityscapes dataset, which is capable of expanding its classes in this case through additional data training

Constraining Very Heavy Dark Matter Using Diffuse Backgrounds of Neutrinos and Cascaded Gamma Rays

We consider multi-messenger constraints on very heavy dark matter (VHDM) from recent Fermi gamma-ray and IceCube neutrino observations of isotropic background radiation. Fermi data on the diffuse gamma-ray background (DGB) shows a possible unexplained feature at very high energies (VHE), which we have called the "VHE Excess" relative to expectations for an attenuated power law extrapolated from lower energies. We show that VHDM could explain this excess, and that neutrino observations will be an important tool for testing this scenario. More conservatively, we derive new constraints on the properties of VHDM for masses of 10^3-10^10 GeV. These generic bounds follow from cosmic energy budget constraints for gamma rays and neutrinos that we developed elsewhere, based on detailed calculations of cosmic electromagnetic cascades and also neutrino detection rates. We show that combining both gamma-ray and neutrino data is essential for making the constraints on VHDM properties both strong and robust. In the lower mass range, our constraints on VHDM annihilation and decay are comparable to other results; however, our constraints continue to much higher masses, where they become relatively stronger.Comment: 33 pages, 21 figures, accepted for publication in JCA

Multi log-normal density structure in Cygnus-X molecular clouds: A fitting for N-PDF without power-law

We studied the H$_2$ column density probability distribution function (N-PDF) based on molecular emission lines using the Nobeyama 45-m Cygnus X CO survey data. Using the DENDROGRAM and SCIMES algorithms, we identified 124 molecular clouds in the $^{13}$CO data. From these identified molecular clouds, an N-PDF was constructed for 11 molecular clouds with an extent of more than 0.4 deg$^2$. From the fitting of the N-PDF, we found that the N-PDF could be well-fitted with one or two log-normal distributions. These fitting results provided an alternative density structure for molecular clouds from a conventional picture. We investigated the column density, dense molecular cloud cores, and radio continuum source distributions in each cloud and found that the N-PDF shape was less correlated with the star-forming activity over a whole cloud. Furthermore, we found that the log-normal N-PDF parameters obtained from the fitting showed two impressive features. First, the log-normal distribution at the low-density part had the same mean column density ($\sim$ 10$^{21.5}$ cm$^{-2}$) for almost all the molecular clouds. Second, the width of the log-normal distribution tended to decrease with an increasing mean density of the structures. These correlations suggest that the shape of the N-PDF reflects the relationship between the density and turbulent structure of the whole molecular cloud but is less affected by star-forming activities.Comment: 14 pages, 7 Figures, Accepted in MNRA