Spurious trend switching phenomena in financial markets

The observation of power laws in the time to extrema of volatility, volume and intertrade times, from milliseconds to years, are shown to result straightforwardly from the selection of biased statistical subsets of realizations in otherwise featureless processes such as random walks. The bias stems from the selection of price peaks that imposes a condition on the statistics of price change and of trade volumes that skew their distributions. For the intertrade times, the extrema and power laws results from the format of transaction data

Quantifying trading behavior in financial markets using Google Trends

Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google query volumes for search terms related to finance, we find patterns that may be interpreted as “early warning signs” of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior

Scanning Raman spectroscopy of graphene antidot lattices: Evidence for systematic p-type doping

We have investigated antidot lattices, which were prepared on exfoliated graphene single layers via electron-beam lithography and ion etching, by means of scanning Raman spectroscopy. The peak positions, peak widths and intensities of the characteristic phonon modes of the carbon lattice have been studied systematically in a series of samples. In the patterned samples, we found a systematic stiffening of the G band mode, accompanied by a line narrowing, while the 2D mode energies are found to be linearly correlated with the G mode energies. We interpret this as evidence for p-type doping of the nanostructured graphene

Transport of Mars-Crossing Asteroids from the Quasi-Hilda Region

We employ set oriented methods in combination with graph partitioning algorithms to identify key dynamical regions in the Sun-Jupiter-particle three-body system. Transport rates from a region near the 3:2 Hilda resonance into the realm of orbits crossing Mars' orbit are computed. In contrast to common numerical approaches, our technique does not depend on single long term simulations of the underlying model. Thus, our statistical results are particularly reliable since they are not affected by a dynamical behavior which is almost nonergodic (i.e., dominated by strongly almost invariant sets)

Crowdsourcing Dialect Characterization through Twitter

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.Comment: 10 pages, 5 figure

Nonequilibrium effects due to charge fluctuations in intrinsic Josephson systems

Nonequilibrium effects in layered superconductors forming a stack of intrinsic Josephson junctions are investigated. We discuss two basic nonequilibrium effects caused by charge fluctuations on the superconducting layers: a) the shift of the chemical potential of the condensate and b) charge imbalance of quasi-particles, and study their influence on IV-curves and the position of Shapiro steps.Comment: 17 pages, 2 figures, revised version slightly shortene

Ventilation area measured with eit in order to optimize peep settings in mechanically ventilated patients

INTRODUCTION. Electrical Impedance Tomography (EIT) is a non-invasive imaging technique, which can be used to visualize ventilation. Ventilation will be measured by impedance changes due to ventilation. OBJECTIVES. The aim of this study was to optimize PEEP settings based on the ventilation area of EIT images during a decremental PEEP trial. METHODS. After a recruitment maneuver, a decremental PEEP trial was performed in 10 mechanically ventilated post cardiac surgery patients. Ventilation area, blood gases, FRC and compliance were measured at each PEEP level. The ventilation area was defined as the surface of ventilation at one lung slice measured with EIT and was expressed as percentage of its maximum obtained during a recruitment maneuver (RM). RESULTS. The amount of ventilated pixels during the RM is set as 100 %. Figure 1 shows the amount of ventilated pixels as percentage compared to its maximum during the RM. The ventilation area was significantly smaller at 5 and 0 PEEP compared to its maximum at both the dependent and non-dependent lung. Also PaO2/FiO2 and FRC were significantly lower at these PEEP levels. (Figure presented) Bars represent the mean + SD. Black = dependent lung region, White = non-dependent lung region. *