Lagrangian properties of eddy fields in the northern North Atlantic as deduced from satellite-tracked buoys

One hundred and thirteen satellite-tracked buoys have been used during their first 5 months after deployment in order to calculate Lagrangian statistics of the eddy field in the northern North Atlantic between Newfoundland and the Canary basin. r.m.s. velocities are isotropic and increase from southeast to northwest. Lagrangian integral time scales, derived both from correlation function and from dispersion, are slightly anisotropic and decrease from the subtropics toward the North Atlantic Current. Time scale is inversely proportional to the r.m.s. velocity of the eddies. Eddy length scale is approximately constant in the North Atlantic. Dispersion is in good agreement with Taylor's hypothesis, following a t2-law during the first day after release and a linear increase with time during days 10 to 60. Eddy diffusivity increases from 30N to 50N by a factor of about 4 and is linearly dependent on the r.m.s. velocity. The energy containing frequency band of the eddies shifts toward higher frequencies in the northern part of the Atlantic. Beyond the cut-off frequency of the eddies the spectral slope follows a -2 or -3 power law

A redshifted Fe Kα\alpha line from the unusual gamma-ray source PMN J1603-4904

Multiwavelength observations have revealed the highly unusual properties of the gamma-ray source PMN J1603-4904, which are difficult to reconcile with any other well established gamma-ray source class. The object is either a very atypical blazar or compact jet source seen at a larger angle to the line of sight. In order to determine the physical origin of the high-energy emission processes in PMN J1603-4904, we study the X-ray spectrum in detail. We performed quasi-simultaneous X-ray observations with XMM-Newton and Suzaku in 2013 September, resulting in the first high signal-to-noise X-ray spectrum of this source. The 2-10 keV X-ray spectrum can be well described by an absorbed power law with an emission line at 5.44$\pm$0.05 keV (observed frame). Interpreting this feature as a K{\alpha} line from neutral iron, we determine the redshift of PMN J1603-4904 to be z=0.18$\pm$0.01, corresponding to a luminosity distance of 872$\pm$54 Mpc. The detection of a redshifted X-ray emission line further challenges the original BL Lac classification of PMN J1603-4904. This result suggests that the source is observed at a larger angle to the line of sight than expected for blazars, and thus the source would add to the elusive class of gamma-ray loud misaligned-jet objects, possibly a {\gamma}-ray bright young radio galaxy.Comment: 5 pages, 1 figure, A&A accepte

Implementation and comparison of algebraic and machine learning based tensor interpolation methods applied to fiber orientation tensor fields obtained from CT images

Fiber orientation tensors (FOT) are used as a compact form of representing the mechanically important quantity of fiber orientation in fiber reinforced composites. While they can be obtained via image processing methods from micro computed tomography scans (CT), the specimen size needs to be sufficiently small for adequate resolution – especially in the case of carbon fibers. In order to avoid massive workload by scans and image evaluation when determining full-field FOT distributions for a plaque or a part, e.g., for comparison with process simulations, the possibilities of a direct interpolation of a few measured FOT at specific support points were opened in this paper. Hence, three different tensor interpolation methods were implemented and compared qualitatively with the help of visualization through tensor glyphs and quantitatively by calculating originally measured tensors at support points and evaluating the deviations. The methods compared in this work include two algebraic approaches, firstly, a Euclidean component averaging and secondly, a decomposition approach based on separate invariant and quaternion weighting, as well as an artificial intelligence (AI)-based method using an artificial neural network (ANN). While the decomposition method showed the best results visually, quantitatively the component averaging method and the neural network behaved better (that is for the type of quantitative error assessment used in this paper) with mean absolute errors of 0.105 and 0.114 when calculating previously measured tensors and comparing the components. With each method providing different advantages, the use for further application as well as necessary improvement is discussed. The authors would like to highlight the novelty of the methods being used with small and CT-based tensor datasets

Single-vehicle data of highway traffic - a statistical analysis

In the present paper single-vehicle data of highway traffic are analyzed in great detail. By using the single-vehicle data directly empirical time-headway distributions and speed-distance relations can be established. Both quantities yield relevant information about the microscopic states. Several fundamental diagrams are also presented, which are based on time-averaged quantities and compared with earlier empirical investigations. In the remaining part time-series analyses of the averaged as well as the single-vehicle data are carried out. The results will be used in order to propose objective criteria for an identification of the different traffic states, e.g. synchronized traffic.Comment: 12 pages, 19 figures, RevTe

Deregulated splicing is a major mechanism of RNA-induced toxicity in Huntington's disease

Huntington's disease (HD) is caused by an expanded CAG repeat in the huntingtin (HTT) gene, translating into an elongated polyglutamine stretch. In addition to the neurotoxic mutant HTT protein, the mutant CAG repeat RNA can exert toxic functions by trapping RNA-binding proteins. While few examples of proteins that aberrantly bind to mutant HTT RNA and execute abnormal function in conjunction with the CAG repeat RNA have been described, an unbiased approach to identify the interactome of mutant HTT RNA is missing. Here, we describe the analysis of proteins that preferentially bind mutant HTT RNA using a mass spectrometry approach. We show that (I) the majority of proteins captured by mutant HTT RNA belong to the spliceosome pathway, (II) expression of mutant CAG repeat RNA induces mis-splicing in a HD cell model, (III) overexpression of one of the splice factors trapped by mutant HTT ameliorates the HD phenotype in a fly model and (VI) deregulated splicing occurs in human HD brain. Our data suggest that deregulated splicing is a prominent mechanism of RNA-induced toxicity in HD

Interpreting the Wide Scattering of Synchronized Traffic Data by Time Gap Statistics

Based on the statistical evaluation of experimental single-vehicle data, we propose a quantitative interpretation of the erratic scattering of flow-density data in synchronized traffic flows. A correlation analysis suggests that the dynamical flow-density data are well compatible with the so-called jam line characterizing fully developed traffic jams, if one takes into account the variation of their propagation speed due to the large variation of the netto time gaps (the inhomogeneity of traffic flow). The form of the time gap distribution depends not only on the density, but also on the measurement cross section: The most probable netto time gap in congested traffic flow upstream of a bottleneck is significantly increased compared to uncongested freeway sections. Moreover, we identify different power-law scaling laws for the relative variance of netto time gaps as a function of the sampling size. While the exponent is -1 in free traffic corresponding to statistically independent time gaps, the exponent is about -2/3 in congested traffic flow because of correlations between queued vehicles.Comment: For related publications see http://www.helbing.or

Cellular automata approach to three-phase traffic theory

The cellular automata (CA) approach to traffic modeling is extended to allow for spatially homogeneous steady state solutions that cover a two dimensional region in the flow-density plane. Hence these models fulfill a basic postulate of a three-phase traffic theory proposed by Kerner. This is achieved by a synchronization distance, within which a vehicle always tries to adjust its speed to the one of the vehicle in front. In the CA models presented, the modelling of the free and safe speeds, the slow-to-start rules as well as some contributions to noise are based on the ideas of the Nagel-Schreckenberg type modelling. It is shown that the proposed CA models can be very transparent and still reproduce the two main types of congested patterns (the general pattern and the synchronized flow pattern) as well as their dependence on the flows near an on-ramp, in qualitative agreement with the recently developed continuum version of the three-phase traffic theory [B. S. Kerner and S. L. Klenov. 2002. J. Phys. A: Math. Gen. 35, L31]. These features are qualitatively different than in previously considered CA traffic models. The probability of the breakdown phenomenon (i.e., of the phase transition from free flow to synchronized flow) as function of the flow rate to the on-ramp and of the flow rate on the road upstream of the on-ramp is investigated. The capacity drops at the on-ramp which occur due to the formation of different congested patterns are calculated.Comment: 55 pages, 24 figure

Derivation, Properties, and Simulation of a Gas-Kinetic-Based, Non-Local Traffic Model

We derive macroscopic traffic equations from specific gas-kinetic equations, dropping some of the assumptions and approximations made in previous papers. The resulting partial differential equations for the vehicle density and average velocity contain a non-local interaction term which is very favorable for a fast and robust numerical integration, so that several thousand freeway kilometers can be simulated in real-time. The model parameters can be easily calibrated by means of empirical data. They are directly related to the quantities characterizing individual driver-vehicle behavior, and their optimal values have the expected order of magnitude. Therefore, they allow to investigate the influences of varying street and weather conditions or freeway control measures. Simulation results for realistic model parameters are in good agreement with the diverse non-linear dynamical phenomena observed in freeway traffic.Comment: For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.html and http://www.theo2.physik.uni-stuttgart.de/treiber.htm