Accelerating, hyperaccelerating, and decelerating networks

Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection. To model sparsely connected networks, we generalize existing approaches and add each new node with a probabilistic number of links to generate either accelerating, hyperaccelerating, or even decelerating network statistics in different regimes. Under preferential attachment for example, slowly accelerating networks display stationary scale-free statistics relatively independent of network size while more rapidly accelerating networks display a transition from scale-free to exponential statistics with network growth. Such transitions explain, for instance, the evolutionary record of single-celled organisms which display strict size and complexity limits

One-dimensional magnetic fluctuations in the spin-2 triangular lattice \alpha-NaMnO2

The S=2 anisotropic triangular lattice alpha-NaMnO2 is studied by neutron inelastic scattering. Antiferromagnetic order occurs at T ~ 45 K with opening of a spin gap. The spectral weight of the magnetic dynamics above the gap (Delta ~ 7.5 meV) has been analysed by the single-mode approximation. Excellent agreement with the experiment is achieved when a dominant exchange interaction (|J|/k_B ~ 73 K), along the monoclinic b-axis and a sizeable easy-axis magnetic anisotropy (|D|/k_B ~ 3 K) are considered. Despite earlier suggestions for two-dimensional spin interactions, the dynamics illustrate strongly coupled antiferromagnetic S=2 chains and cancellation of the interchain exchange due to the lattice topology. alpha-NaMnO2 therefore represents a model system where the geometric frustration is resolved through the lowering of the dimensionality of the spin interactions.Comment: 4 pages, 4 figures, to be published in Physical Review Letter

Improving Fission-product Decay Data for Reactor Applications: Part I -- Decay Heat

Effort has been expended to assess the relative merits of undertaking further decay-data measurements of the main fission-product contributors to the decay heat of neutron-irradiated fissile fuel and related actinides by means of Total Absorption Gamma-ray Spectroscopy (TAGS/TAS) and Discrete Gamma-ray Spectroscopy (DGS). This review has been carried out following similar work performed under the auspices of OECD/WPEC-Subgroup 25 (2005-2007) and the International Atomic Energy Agency (2010, 2014), and various highly relevant TAGS measurements completed as a consequence of such assessments. We present our recommendations for new decay-data evaluations, along with possible requirements for total absorption and discrete high-resolution gamma-ray spectroscopy studies that cover approximately 120 fission products and various isomeric states.Comment: Submitted to European Physical Journal

SoLid : Search for Oscillations with Lithium-6 Detector at the SCK-CEN BR2 reactor

Sterile neutrinos have been considered as a possible explanation for the recent reactor and Gallium anomalies arising from reanalysis of reactor flux and calibration data of previous neutrino experiments. A way to test this hypothesis is to look for distortions of the anti-neutrino energy caused by oscillation from active to sterile neutrino at close stand-off (similar to 6-8m) of a compact reactor core. Due to the low rate of anti-neutrino interactions the main challenge in such measurement is to control the high level of gamma rays and neutron background. The SoLid experiment is a proposal to search for active-to-sterile anti-neutrino oscillation at very short baseline of the SCK center dot CEN BR2 research reactor. This experiment uses a novel approach to detect anti-neutrino with a highly segmented detector based on Lithium-6. With the combination of high granularity, high neutron-gamma discrimination using 6LiF:ZnS(Ag) and precise localization of the Inverse Beta Decay products, a better experimental sensitivity can be achieved compared to other state-of-the-art technology. This compact system requires minimum passive shielding allowing for very close stand off to the reactor. The experimental set up of the SoLid experiment and the BR2 reactor will be presented. The new principle of neutrino detection and the detector design with expected performance will be described. The expected sensitivity to new oscillations of the SoLid detector as well as the first measurements made with the 8 kg prototype detector deployed at the BR2 reactor in 2013-2014 will be reported

Asymmetry, realised volatility and stock return risk estimates

In this paper we estimate minimum capital risk requirements for short and long positions with three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes. We also address the problem of the extremely high estimated persistence of the GARCH model to generate observed volatility patterns by including realised volatility as an explanatory variable into the model’s variance equation. The results suggest that the inclusion of realised volatility improves the GARCH forecastability as well as its ability to calculate accurate minimum capital risk requirements and makes it quite competitive when compared with asymmetric conditional heteroscedastic models such as the GJR and the EGARCH.info:eu-repo/semantics/publishedVersio

Online Monitoring of the Osiris Reactor with the Nucifer Neutrino Detector

Originally designed as a new nuclear reactor monitoring device, the Nucifer detector has successfully detected its first neutrinos. We provide the second shortest baseline measurement of the reactor neutrino flux. The detection of electron antineutrinos emitted in the decay chains of the fission products, combined with reactor core simulations, provides an new tool to assess both the thermal power and the fissile content of the whole nuclear core and could be used by the Inter- national Agency for Atomic Energy (IAEA) to enhance the Safeguards of civil nuclear reactors. Deployed at only 7.2m away from the compact Osiris research reactor core (70MW) operating at the Saclay research centre of the French Alternative Energies and Atomic Energy Commission (CEA), the experiment also exhibits a well-suited configuration to search for a new short baseline oscillation. We report the first results of the Nucifer experiment, describing the performances of the 0.85m3 detector remotely operating at a shallow depth equivalent to 12m of water and under intense background radiation conditions. Based on 145 (106) days of data with reactor ON (OFF), leading to the detection of an estimated 40760 electron antineutrinos, the mean number of detected antineutrinos is 281 +- 7(stat) +- 18(syst) electron antineutrinos/day, in agreement with the prediction 277(23) electron antineutrinos/day. Due the the large background no conclusive results on the existence of light sterile neutrinos could be derived, however. As a first societal application we quantify how antineutrinos could be used for the Plutonium Management and Disposition Agreement.Comment: 22 pages, 16 figures - Version

Forecasting Daily Variability of the S and P 100 Stock Index using Historical, Realised and Implied Volatility Measurements

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved volatility measurements but has also inspired research into their potential value as an information source for volatility forecasting. In this paper we explore the forecasting value of historical volatility (extracted from daily return series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of squared high frequency returns within a day). First we consider unobserved components and long memory models for realised volatility which is regarded as an accurate estimator of volatility. The predictive abilities of realised volatility models are compared with those of stochastic volatility models and generalised autoregressive conditional heteroskedasticity models for daily return series. These historical volatility models are extended to include realised and implied volatility measures as explanatory variables for volatility. The main focus is on forecasting the daily variability of the Standard and Poor's 100 stock index series for which trading data (tick by tick) of almost seven years is analysed. The forecast assessment is based on the hypothesis of whether a forecast model is outperformed by alternative models. In particular, we will use superior predictive ability tests to investigate the relative forecast performances of some models. Since volatilities are not observed, realised volatility is taken as a proxy for actual volatility and is used for computing the forecast error. A stationary bootstrap procedure is required for computing the test statistic and its $p$-value. The empirical results show convincingly that realised volatility models produce far more accurate volatility forecasts compared to models based on daily returns. Long memory models seem to provide the most accurate forecasts

Reuse of structural domain–domain interactions in protein networks

<p>Abstract</p> <p>Background</p> <p>Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as <it>i</it>Pfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the <it>i</it>Pfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases.</p> <p>Results</p> <p>We find that known structural domain interactions can only explain a subset of 4–19% of the available protein interactions, nevertheless this fraction is still significantly bigger than expected by chance. There is a correlation between the frequency of a domain interaction and the connectivity of the proteins it occurs in. Furthermore, a large proportion of protein interactions can be attributed to a small number of domain interactions. We conclude that many, but not all, domain interactions constitute reusable modules of molecular recognition. A substantial proportion of domain interactions are conserved between <it>E. coli</it>, <it>S. cerevisiae </it>and <it>H. sapiens</it>. These domains are related to essential cellular functions, suggesting that many domain interactions were already present in the last universal common ancestor.</p> <p>Conclusion</p> <p>Our results support the concept of domain interactions as reusable, conserved building blocks of protein interactions, but also highlight the limitations currently imposed by the small number of available protein structures.</p