DYRE: a DYnamic REconfigurable solution to increase GPGPU’s reliability

The Journal of Supercomputing - General-purpose graphics processing units (GPGPUs) are extensively used in high-performance computing. However, it is well known that these devices’...     

P distribution in different sediment fraction of a constructed wetland

The aim of this work was to study the accumulation and fractionation of P in the inlet and outlet sediment of a constructed wetland for the wastewater treatment of a metallurgic plant in Argentina. It was important to predict whether P could be released into the water again by changing environmental conditions or retained over time. P-fractionation was performed using a sequential extraction method. Sediment cores were sliced at depths of: 0-3; 3-7 and 7-10 cm. Sediment showed high pH values and anoxic conditions. In the inlet area, P was principally bound to the carbonate fraction, whereas in the outlet area, it was mainly bound in the residual fraction. This behavior was justified by the effluent composition, which is rich in Ca2+ and Fe3+ and presents high values of pH and conductivity. These conditions favor CaCO3 and Fe(OOH)n precipitation and the subsequent sorption of P to their surface. The sediment active layer involved in the exchange reactions was the superficial one (0-3 cm). The wetland is highly efficient in P retention. P was retained by sediment in fractions that will not release it to the water while chemical and environmental conditions of the system are maintained.     

Sound synthesis and evaluation of interactive footsteps and environmental sounds rendering for virtual reality applications

We propose a system that affords real-time sound synthesis of footsteps on different materials. The system is based on microphones, which detect real footstep sounds from subjects, from which the ground reaction force (GRF) is estimated. Such GRF is used to control a sound synthesis engine based on physical models. Two experiments were conducted. In the first experiment, the ability of subjects to recognize the surface they were exposed to was assessed. In the second experiment, the sound synthesis engine was enhanced with environmental sounds. Results show that, in some conditions, adding a soundscape significantly improves the recognition of the simulated environment.     

Generalization in the XCSF classifier system: analysis, improvement, and extension

We analyze generalization in XCSF and introduce three improvements. We begin by showing that the types of generalizations evolved by XCSF can be influenced by the input range. To explain these results we present a theoretical analysis of the convergence of classifier weights in XCSF which highlights a broader issue. In XCSF, because of the mathematical properties of the Widrow-Hoff update, the convergence of classifier weights in a given subspace can be slow when the spread of the eigenvalues of the autocorrelation matrix associated with each classifier is large. As a major consequence, the system's accuracy pressure may act before classifier weights are adequately updated, so that XCSF may evolve piecewise constant approximations, instead of the intended, and more efficient, piecewise linear ones. We propose three different ways to update classifier weights in XCSF so as to increase the generalization capabilities of XCSF: one based on a condition-based normalization of the inputs, one based on linear least squares, and one based on the recursive version of linear least squares. Through a series of experiments we show that while all three approaches significantly improve XCSF, least squares approaches appear to be best performing and most robust. Finally we show how XCSF can be extended to include polynomial approximations.     

First-Void Urine Microbiome in Women with Chlamydia trachomatis Infection

Background: Chlamydia trachomatis (CT) is the agent of the most common bacterial sexually transmitted infection worldwide. Until now, little information is available about the microbial composition of urine samples during CT urethritis. Therefore, in this study, we characterized the microbiome and metabolome profiles of first-void urines in a cohort of women with CT urethral infection attending an STI clinic. Methods: Based on CT positivity by nucleic acid amplification techniques on urine samples, the enrolled women were divided into two groups, i.e., “CT-negative” (n = 21) and “CT-positive” (n = 11). Urine samples were employed for (i) the microbiome profile analysis by means of 16s rRNA gene sequencing and (ii) the metabolome analysis by ¹H-NMR. Results: Irrespective of CT infection, the microbiome of first-void urines was mainly dominated by Lactobacillus, L. iners and L. crispatus being the most represented species. CT-positive samples were characterized by reduced microbial biodiversity compared to the controls. Moreover, a significant reduction of the Mycoplasmataceae family—in particular, of the Ureaplasma parvum species—was observed during CT infection. The Chlamydia genus was positively correlated with urine hippurate and lactulose. Conclusions: These data can help elucidate the pathogenesis of chlamydial urogenital infections, as well as to set up innovative diagnostic and therapeutic approaches.     

An efficient distributed algorithm for generating and updating multicast trees

As group applications are becoming widespread, efficient network utilization becomes a growing concern. Multicast transmission represents a necessary lower network service for the wide diffusion of new multimedia network applications. Multicast transmission may use network resources more efficiently than multiple point-to-point messages; however, creating optimal multicast trees (Steiner Tree Problem in networks) is prohibitively expensive. This paper proposes a distributed algorithm for the heuristic solution of the Steiner Tree Problem, allowing the construction of effective distribution trees using a coordination protocol among the network nodes. Furthermore, we propose a novel distributed technique for dynamically updating the multicast tree. The approach proposed has been implemented and extensively tested both in simulation, and on experimental networks. Performance evaluation indicates that the distributed algorithm performs as well as the centralized version, providing good levels of convergence time and communication complexity.     

ICOSL Stimulation by ICOS-Fc Accelerates Cutaneous Wound Healing In Vivo

Background: ICOS and its ligand ICOSL are immune receptors whose interaction triggers bidirectional signals that modulate the immune response and tissue repair. Aim: The aim of this study was to assess the in vivo effects of ICOSL triggering by ICOS-Fc, a recombinant soluble form of ICOS, on skin wound healing. Methods: The effect of human ICOS-Fc on wound healing was assessed, in vitro, and, in vivo, by skin wound healing assay using ICOS^−/− and ICOSL^−/− knockout (KO) mice and NOD-SCID-IL2R null (NSG) mice. Results: We show that, in wild type mice, treatment with ICOS-Fc improves wound healing, promotes angiogenesis, preceded by upregulation of IL-6 and VEGF expression; increases the number of fibroblasts and T cells, whereas it reduces that of neutrophils; and increases the number of M2 vs. M1 macrophages. Fittingly, ICOS-Fc enhanced M2 macrophage migration, while it hampered that of M1 macrophages. ICOS^−/− and ICOSL^−/− KO, and NSG mice showed delayed wound healing, and treatment with ICOS-Fc improved wound closure in ICOS^−/− and NSG mice. Conclusion: These data show that the ICOS/ICOSL network cooperates in tissue repair, and that triggering of ICOSL by ICOS-Fc improves cutaneous wound healing by increasing angiogenesis and recruitment of reparative macrophages.