TESTING THE EFFICIENCY OF MARKETS IN THE 2002 WORLD CUP

Trading data from the gambling market for the 2002 World Cup provide a unique window through which to test theories of market efficiency.  This market provides many of the benefits of a laboratory experiment, but with much higher stakes, experienced participants, and a naturally-occurring environment.  The primary drawback of the data is the relatively small number of trades.  The evidence concerning market efficiency is mixed.  Although markets respond strongly to goals being scored, there is some evidence that prices continue to trend higher for 10-15 minutes after a goal.  We also observe systematically negative returns for bets on the pre-game favorite, consistent with the biases seen in wagering on other sports.  We document the endogenous emergence of market makers.  These market makers are involved in a large share of trades.  Increasing from two active market makers to five or more market makers does not appear to improve the functioning of the market.  On average, the market makers earn slightly negative returns, implying that other traders are able to identify situations in which market makers are setting inefficient price

The Morphospace of Consciousness

We construct a complexity-based morphospace to study systems-level properties of conscious & intelligent systems. The axes of this space label 3 complexity types: autonomous, cognitive & social. Given recent proposals to synthesize consciousness, a generic complexity-based conceptualization provides a useful framework for identifying defining features of conscious & synthetic systems. Based on current clinical scales of consciousness that measure cognitive awareness and wakefulness, we take a perspective on how contemporary artificially intelligent machines & synthetically engineered life forms measure on these scales. It turns out that awareness & wakefulness can be associated to computational & autonomous complexity respectively. Subsequently, building on insights from cognitive robotics, we examine the function that consciousness serves, & argue the role of consciousness as an evolutionary game-theoretic strategy. This makes the case for a third type of complexity for describing consciousness: social complexity. Having identified these complexity types, allows for a representation of both, biological & synthetic systems in a common morphospace. A consequence of this classification is a taxonomy of possible conscious machines. We identify four types of consciousness, based on embodiment: (i) biological consciousness, (ii) synthetic consciousness, (iii) group consciousness (resulting from group interactions), & (iv) simulated consciousness (embodied by virtual agents within a simulated reality). This taxonomy helps in the investigation of comparative signatures of consciousness across domains, in order to highlight design principles necessary to engineer conscious machines. This is particularly relevant in the light of recent developments at the crossroads of cognitive neuroscience, biomedical engineering, artificial intelligence & biomimetics.Comment: 23 pages, 3 figure

Synthetic Turing protocells: vesicle self-reproduction through symmetry-breaking instabilities

The reproduction of a living cell requires a repeatable set of chemical events to be properly coordinated. Such events define a replication cycle, coupling the growth and shape change of the cell membrane with internal metabolic reactions. Although the logic of such process is determined by potentially simple physico-chemical laws, the modeling of a full, self-maintained cell cycle is not trivial. Here we present a novel approach to the problem which makes use of so called symmetry breaking instabilities as the engine of cell growth and division. It is shown that the process occurs as a consequence of the breaking of spatial symmetry and provides a reliable mechanism of vesicle growth and reproduction. Our model opens the possibility of a synthetic protocell lacking information but displaying self-reproduction under a very simple set of chemical reactions

Decoherence in supernova neutrino transformations suppressed by deleptonization

In the dense-neutrino region at 50-400 km above the neutrino sphere in a supernova, neutrino-neutrino interactions cause large flavor transformations. We study when the multi-angle nature of the neutrino trajectories leads to flavor decoherence between different angular modes. We consider a two-flavor mixing scenario between nu_e and another flavor nu_x and assume the usual hierarchy F(nu_e)>F{antinu_e)>F(nu_x)=F(antinu_x) for the number fluxes. We define epsilon=(F(nu_e)-F(antinu_e))/(F(antinu_e)-F(antinu_x)) as a measure for the deleptonization flux which is the one crucial parameter. The transition between the quasi single-angle behavior and multi-angle decoherence is abrupt as a function of epsilon. For typical choices of other parameters, multi-angle decoherence is suppressed for epsilon>0.3, but a much smaller asymmetry suffices if the neutrino mass hierarchy is normal and the mixing angle small. The critical epsilon depends logarithmically on the neutrino luminosity. In a realistic supernova scenario, the deleptonization flux is probably enough to suppress multi-angle decoherence.Comment: 17 pages, 12 figures. Misprint in Eq (14) correcte

An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 5 project (Que´bec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in 10 Southern Que´bec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs’ members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows

On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff

In climate change impact research, the assessment of future river runoff as well as the catchment scale water balance is impeded by different sources of modeling uncertainty. Some research has already been done in order to quantify the uncertainty of climate 5 projections originating from the climate models and the downscaling techniques as well as from the internal variability evaluated from climate model member ensembles. Yet, the use of hydrological models adds another layer of incertitude. Within the QBic3 project (Qu´ebec-Bavaria International Collaboration on Climate Change) the relative contributions to the overall uncertainty from the whole model chain (from global climate 10 models to water management models) are investigated using an ensemble of multiple climate and hydrological models. Although there are many options to downscale global climate projections to the regional scale, recent impact studies tend to use Regional Climate Models (RCMs). One reason for that is that the physical coherence between atmospheric and land-surface 15 variables is preserved. The coherence between temperature and precipitation is of particular interest in hydrology. However, the regional climate model outputs often are biased compared to the observed climatology of a given region. Therefore, biases in those outputs are often corrected to reproduce historic runoff conditions from hydrological models using them, even if those corrections alter the relationship between temperature and precipitation. So, as bias correction may affect the consistency between RCM output variables, the use of correction techniques and even the use of (biased) climate model data itself is sometimes disputed among scientists. For those reasons, the effect of bias correction on simulated runoff regimes and the relative change in selected runoff indicators is explored. If it affects the conclusion of climate change analysis in 25 hydrology, we should consider it as a source of uncertainty. If not, the application of bias correction methods is either unnecessary in hydro-climatic projections, or safe to use as it does not alter the change signal of river runoff. The results of the present paper highlight the analysis of daily runoff simulated with four different hydrological models in two natural-flow catchments, driven by different regional climate models for a reference and a future period. As expected, bias correction of climate model outputs is important for the reproduction of the runoff regime of the 5 past regardless of the hydrological model used. Then again, its impact on the relative change of flow indicators between reference and future period is weak for most indicators with the exception of the timing of the spring flood peak. Still, our results indicate that the impact of bias correction on runoff indicators increases with bias in the climate simulations

Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners

Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (Dmax: 11.7 nm, Rg: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway

Exactness of the Fock space representation of the q-commutation relations

We show that for all q in the interval (-1,1), the Fock representation of the q-commutation relations can be unitarily embedded into the Fock representation of the extended Cuntz algebra. In particular, this implies that the C*-algebra generated by the Fock representation of the q-commutation relations is exact. An immediate consequence is that the q-Gaussian von Neumann algebra is weakly exact for all q in the interval (-1,1).Comment: 20 page