One-point fluctuation analysis of IceCube neutrino events outlines a significant unassociated isotropic component and constrains the Galactic contribution

The origins of the extraterrestrial neutrinos observed in IceCube have yet to be determined. In this study we perform a one-point fluctuation analysis of the six-year high-energy starting event (HESE) shower data, with fixed non-Poissonian contributions from atmospheric, Galactic and some extragalactic components, as well as an isotropic (and weakly non-Poissonian) template. In addition to the star-forming galaxies and blazars, our analysis suggests the presence of an additional isotropic component, not associated with any known class of sources, with best-fit intensity of $(2.8\pm0.2)\times 10^{-18}\,(E/100~{\rm TeV})^{-2.7\pm 0.5}$ ${\mathrm{cm}^{-2}\, \mathrm{s}^{-1}\,\mathrm{sr}^{-1}\,\mathrm{GeV}^{-1}}$. For the first time, we also consider high-energy extrapolations of several phenomenological models for the diffuse Galactic emission (tuned to both local cosmic-ray data and diffuse gamma-ray emission in the GeV-TeV domain). We demonstrate the potential of our framework in discriminating between different scenarios, with possible implications on the physics of cosmic ray transport in the TeV-PeV range.Comment: 10 pages, 3 figures, accepted for publication in PR

Diversity analysis, code design, and tight error rate lower bound for binary joint network-channel coding

Joint network-channel codes (JNCC) can improve the performance of communication in wireless networks, by combining, at the physical layer, the channel codes and the network code as an overall error-correcting code. JNCC is increasingly proposed as an alternative to a standard layered construction, such as the OSI-model. The main performance metrics for JNCCs are scalability to larger networks and error rate. The diversity order is one of the most important parameters determining the error rate. The literature on JNCC is growing, but a rigorous diversity analysis is lacking, mainly because of the many degrees of freedom in wireless networks, which makes it very hard to prove general statements on the diversity order. In this article, we consider a network with slowly varying fading point-to-point links, where all sources also act as relay and additional non-source relays may be present. We propose a general structure for JNCCs to be applied in such network. In the relay phase, each relay transmits a linear transform of a set of source codewords. Our main contributions are the proposition of an upper and lower bound on the diversity order, a scalable code design and a new lower bound on the word error rate to assess the performance of the network code. The lower bound on the diversity order is only valid for JNCCs where the relays transform only two source codewords. We then validate this analysis with an example which compares the JNCC performance to that of a standard layered construction. Our numerical results suggest that as networks grow, it is difficult to perform significantly better than a standard layered construction, both on a fundamental level, expressed by the outage probability, as on a practical level, expressed by the word error rate

Scientometric mapping as a strategic intelligence tool for the governance of emerging technologies

How can scientometric mapping function as a tool of ’strategic intelligence’ to aid the governance of emerging technologies? The present paper aims to address this question by focusing on a set of recently developed scientometric techniques, namely overlay mapping. We examine the potential these techniques have to inform, in a timely manner, analysts and decision-makers about relevant dynamics of technical emergence. We investigate the capability of overlay mapping in generating informed perspectives about emergence across three spaces: geographical, social, and cognitive. Our analysis relies on three empirical studies of emerging technologies in the biomedical domain: RNA interference (RNAi), Human Papilloma Virus (HPV) testing technologies for cervical cancer, and Thiopurine Methyltransferase (TPMT) genetic testing. The case-studies are analysed and mapped longitudinally by using publication and patent data. Results show the variety of ’intelligence’ inputs overlay mapping can produce for the governance of emerging technologies. Overlay mapping also confers to the investigation of emergence flexibility and granularity in terms of adaptability to different sources of data and selection of the levels of the analysis, respectively. These features make possible the integration and comparison of results from different contexts and cases, thus providing possibilities for a potentially more ’distributed’ strategic intelligence. The generated perspectives allow triangulation of findings, which is important given the complexity featuring in technical emergence and the limitations associated with the use of single scientometric approaches

Engineering single-molecule, nanoscale, and microscale bio-functional materials via click chemistry

To expand the design envelope and supplement the materials library available to biomaterials scientists, the copper(I)-catalyzed azide-alkyne cycloaddition (CuCAAC) was explored as a route to design, synthesize and characterize bio-functional small-molecules, nanoparticles, and microfibers. In each engineered system, the use of click chemistry provided facile, bio-orthogonal control for materials synthesis; moreover, the results provided a methodology and more complete, fundamental understanding of the use of click chemistry as a tool for the synergy of biotechnology, polymer and materials science. Fluorophores with well-defined photophysical characteristics (ranging from UV to NIR fluorescence) were used as building blocks for small-molecule, fluorescent biosensors. Fluorophores were paired to exhibit fluorescence resonant energy transfer (FRET) and used to probe the metabolic activity of carbazole 1,9a-dioxygenase (CARDO). The FRET pair exhibited a signicant variation in PL response with exposure to the lysate of Pseudomonas resinovorans CA10, an organism which can degrade variants of both the donor and acceptor fluorophores. Nanoparticle systems were modified via CuCAAC chemistry to carry affinity tags for CARDO and were subsequently utilized for affinity based bioseparation of CARDO from crude cell lysate. The enzymes were baited with an azide-modified carbazolyl-moiety attached to a poly(propargyl acrylate) nanoparticle. Magnetic nanocluster systems were also modified via CuCAAC chemistry to carry fluorescent imaging tags. The iron-oxide nanoclusters were coated with poly(acrylic acid-co-propargyl acrylate) to provide a clickable surface. Ultimately, alternate Cu-free click chemistries were utilized to produce biohybrid microfibers. The biohybrid microfibers were synthesized under benign photopolymerization conditions inside a microchannel, allowing the encapsulation of viable bacteria. By adjusting pre-polymer solutions and laminar flow rates within the microchannel, the morphology, hydration, and thermal properties of the fibers were easily tuned. The methodology produced hydrogel fibers that sustained viable cells as demonstrated by the encapsulation and subsequent proliferation of Bacillus cereus and Escherichia coli communities

Modeling brain dynamics in brain tumor patients using the virtual brain

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance

Elevational diversity of terrestrial rainforest herbs: when the whole is less than the sum of its parts

We studied the species richness of herbaceous terrestrial plant species along an elevational gradient at 250-2425m a.s.l. in evergreen tropical forest in Central Sulawesi, Indonesia. We recorded 302 species belonging to 51 families. Ferns and lycophytes contributed 62% of the species, followed by monocots with 24% and dicots with 14%. Overall herb species richness did not show any particular relation with elevation, while the richness of ferns increased significantly with elevation, monocots did not show a pattern, and dicots showed a hump-shaped pattern with maximum richness at 1800m. These patterns in turn were only partly reflected in the patterns of the individual plant families making up each group. The independence of different taxa was also reflected in their relationships to environmental factors (temperature, precipitation, and area): although, each single family was related to one or several factors, at the group level and at the overall level these trends were lost. These results show that interpreting diversity at higher taxonomic level may overlook important information at the family level and raises the biologically intriguing question whether overall patterns of diversity result from a random accumulation of group-specific patterns or if there is some interaction between groups (e.g., via competition and niche-pre-emption