Castleman disease and lymphocytic interstitial pneumonia: a complex diagnostic and management challenge

No abstract available

A New Galaxy in the Local Group: the Antlia Dwarf Galaxy

We report the discovery of new member of the Local Group in the constellation of Antlia. Optically the system appears to be a typical dwarf spheroidal galaxy of type dE3.5 with no apparent young blue stars or unusual features. A color-magnitude diagram in I, V-I shows the tip of the red giant branch, giving a distance modulus of 25.3 +/- 0.2 (1.15 Mpc +/- 0.1) and a metallicity of -1.6 +/- 0.3. Although Antlia is in a relatively isolated part of the Local Group it is only 1.2 degrees away on the sky from the Local Group dwarf NGC3109, and may be an associated system.Comment: AJ in press, 15 pages, 7 figures, figure 2 in b/w for space saving, full postscript version available at http://www.ast.cam.ac.uk/~gkth/antlia-pp.htm

Light Element Synthesis in High Entropy Relativistic Flows Associated with Gamma Ray Bursts

We calculate and discuss the light element freeze-out nucleosynthesis in high entropy winds and fireballs for broad ranges of entropy-per-baryon, dynamic timescales characterizing relativistic expansion, and neutron-to-proton ratios. With conditions characteristic of Gamma Ray Bursts (GRBs) we find that deuterium production can be prodigious, with final abundance values 2H/H approximately 2%, depending on the fireball isospin, late time dynamics, and the effects of neutron decoupling- induced high energy non-thermal nuclear reactions. This implies that there potentially could be detectable local enhancements in the deuterium abundance associated with GRB events.Comment: 14 pages 3 figure

The Human Thioesterase II Protein Binds to a Site on HIV-1 Nef Critical for CD4 Down-regulation

A HIV-1 Nef affinity column was used to purify a 35-kDa Nef-interacting protein from T-cell lysates. The 35-kDa protein was identified by peptide microsequence analysis as the human thioesterase II (hTE) enzyme, an enzyme previously identified in a yeast two-hybrid screen as a potential Nef-interacting protein. Immunofluorescence studies showed that hTE localizes to peroxisomes and that coexpression of Nef and hTE leads to relocalization of Nef to peroxisomes. Interaction of Nef and hTE was abolished by point mutations in Nef at residues Asp108, Leu112, Phe121, Pro122, and Asp123. All of these mutations also abrogated the ability of Nef to down-regulate CD4 from the surface of HIV-infected cells. Based on the x-ray and NMR structures of Nef, these residues define a surface on Nef critical for CD4 down-regulation. A subset of these mutations also affected the ability of Nef to down-regulate major histocompatibility complex class I. These results, taken together with previous studies, identify a region on Nef critical for most of its known functions. However, not all Nef alleles bind to hTE with high affinity, so the role of hTE during HIV infection remains uncertain

t-J model of coupled Cu2_2O5_5 ladders in Sr14−x_{14-x}Cax_xCu24_{24}O41_{41}

Starting from the proper charge transfer model for Cu$_2$O$_5$ coupled ladders in Sr$_{14-x}$Ca$_x$Cu$_{24}$O$_{41}$ we derive the low energy Hamiltonian for this system. It occurs that the widely used ladder t-J model is not sufficient and has to be supplemented by the Coulomb repulsion term between holes in the neighboring ladders. Furthermore, we show how a simple mean-field solution of the derived t-J model may explain the onset of the charge density wave with the odd period in Sr$_{14-x}$Ca$_x$Cu$_{24}$O$_{41}$.Comment: 8 pages, 4 figures, 2 table

Striking Photospheric Abundance Anomalies in Blue Horizontal-Branch Stars in Globular Cluster M13

High-resolution optical spectra of thirteen blue horizontal-branch (BHB) stars in the globular cluster M13 show enormous deviations in element abundances from the expected cluster metallicity. In the hotter stars (T_eff > 12000 K), helium is depleted by factors of 10 to 100 below solar, while iron is enhanced to three times the solar abundance, two orders of magnitude above the canonical metallicity [Fe/H] ~= -1.5 dex for this globular cluster. Nitrogen, phosphorus, and chromium exhibit even more pronounced enhancements, and other metals are also mildly overabundant, with the exception of magnesium, which stays very near the expected cluster metallicity. These photospheric anomalies are most likely due to diffusion --- gravitational settling of helium, and radiative levitation of the other elements --- in the stable radiative atmospheres of these hot stars. The effects of these mechanisms may have some impact on the photometric morphology of the cluster's horizontal branch and on estimates of its age and distance.Comment: 11 pages, 1 Postscript figure, uses aaspp4.sty, accepted for publication in ApJ Letter

The Species Concordance Method of Tide Prediction in Estuaries

The harmonic method of tide prediction is developed to its fullest extent, so that it can deal with tide curves which are so distorted that they have gradient discontinuities. It is better, however, to use a new two-step method known as the method of species concordance. This method is applied to the Gironde, and then to the Loire, where the variation in fresh-water level is important

Hypervolume Sen Task Scheduilng and Multi Objective Deep Auto Encoder based Resource Allocation in Cloud

Cloud Computing (CC) environment has restructured the Information Age by empowering on demand dispensing of resources on a pay-per-use base. Resource Scheduling and allocation is an approach of ascertaining schedule on which tasks should be carried out. Owing to the heterogeneity nature of resources, scheduling of resources in CC environment is considered as an intricate task. Allocating best resource for a cloud request remains a complicated task and the issue of identifying the best resource – task pair according to user requirements is considered as an optimization issue. Therefore the main objective of the Cloud Server remains in scheduling the tasks and allocating the resources in an optimal manner. In this work an optimized task scheduled resource allocation model is designed to effectively address  large numbers of task request arriving from cloud users, while maintaining enhanced Quality of Service (QoS). The cloud user task requests are mapped in an optimal manner to cloud resources. The optimization process is carried out using the proposed Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) method which is a combination of Sen’s Multi-objective functions and Auto-encoder Deep Neural Network model. First tasks scheduling is performed by applying Hypervolume-based Sen’s Multi-objective programming model. With this, multi-objective optimization (i.e., optimization of cost and time during the scheduling of tasks) is performed by means of Hypervolume-based Sen’s Multi-objective programming. Second, Auto-encoder Deep Neural Network-based Resource allocation is performed with the scheduled tasks that in turn allocate the resources by utilizing Jensen–Shannon divergence function. The Jensen–Shannon divergence function has the advantage of minimizing the energy consumption that only with higher divergence results, mapping is performed, therefore improving the energy consumption to a greater extent. Finally, mapping tasks with the corresponding resources using Kronecker Delta function improves the makespan significantly. To show the efficiency of Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) cloud time scheduling and optimization between tasks and resources in the CC environment, we also perform thorough experiments on the basis of realistic traces derived from Personal Cloud Datasets. The experimental results show that compared with RAA-PI-NSGAII and DRL, MA-DNN not only significantly accelerates the task scheduling efficiency, task scheduling time but also reduces the energy usage and makespan considerably

Unlocking the deployment of spectrum sharing with a policy enforcement framework

Spectrum sharing has been proposed as a promising way to increase the efficiency of spectrum usage by allowing incumbent operators (IOs) to share their allocated radio resources with licensee operators (LOs), under a set of agreed rules. The goal is to maximize a common utility, such as the sum rate throughput, while maintaining the level of service required by the IOs. However, this is only guaranteed under the assumption that all “players”respect the agreed sharing rules. In this paper, we propose a comprehensive framework for licensed shared access (LSA) networks that discourages LO misbehavior. Our framework is built around three core functions: misbehavior detection via the employment of a dedicated sensing network; a penalization function; and, a behavior-driven resource allocation. To the best of our knowledge, this is the first time that these components are combined for the monitoring/policing of the spectrum under the LSA framework. Moreover, a novel simulator for LSA is provided as an open access tool, serving the purpose of testing and validating our proposed techniques via a set of extensive system-level simulations in the context of mobile network operators, where IOs and several competing LOs are considered. The results demonstrate that violation of the agreed sharing rules can lead to a great loss of resources for the misbehaving LOs, the amount of which is controlled by the system. Finally, we promote that including a policy enforcement function as part of the spectrum sharing system can be beneficial for the LSA system, since it can guarantee compliance with the spectrum sharing rules and limit the short-term benefits arising from misbehavior