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Two-particle angular correlations were measured in pp collisions at s√=7 TeV. The analysis was carried out for pions, kaons, protons, and lambdas, for all particle/anti-particle combinations in the pair. Data for mesons exhibit an expected peak dominated by effects associated with mini-jets and are well reproduced by general purpose Monte Carlo generators. However, for baryon--baryon and anti-baryon--anti-baryon pairs, where both particles have the same baryon number, a near-side anti-correlation structure is observed instead of a peak. This effect is interpreted in the context of baryon production mechanisms in the fragmentation process. It currently presents a challenge to Monte Carlo models and its origin remains an open question.
We present the charged-particle pseudorapidity density in Pb-Pb collisions at sNN−−−√=5.02TeV in centrality classes measured by ALICE. The measurement covers a wide pseudorapidity range from −3.5 to 5, which is sufficient for reliable estimates of the total number of charged particles produced in the collisions. For the most central (0-5%) collisions we find 21400±1300 while for the most peripheral (80-90%) we find 230±38. This corresponds to an increase of (27±4)% over the results at sNN−−−√=2.76TeV previously reported by ALICE. The energy dependence of the total number of charged particles produced in heavy-ion collisions is found to obey a modified power-law like behaviour. The charged-particle pseudorapidity density of the most central collisions is compared to model calculations --- none of which fully describes the measured distribution. We also present an estimate of the rapidity density of charged particles. The width of that distribution is found to exhibit a remarkable proportionality to the beam rapidity, independent of the collision energy from the top SPS to LHC energies.
Abstract: Integration of synaptic currents across an extensive dendritic tree is a prerequisite for computation in the brain. Dendritic tapering away from the soma has been suggested to both equalise contributions from synapses at different locations and maximise the current transfer to the soma. To find out how this is achieved precisely, an analytical solution for the current transfer in dendrites with arbitrary taper is required. We derive here an asymptotic approximation that accurately matches results from numerical simulations. From this we then determine the diameter profile that maximises the current transfer to the soma. We find a simple quadratic form that matches diameters obtained experimentally, indicating a fundamental architectural principle of the brain that links dendritic diameters to signal transmission.
Author Summary: Neurons take a great variety of shapes that allow them to perform their different computational roles across the brain. The most distinctive visible feature of many neurons is the extensively branched network of cable-like projections that make up their dendritic tree. A neuron receives current-inducing synaptic contacts from other cells across its dendritic tree. As in the case of botanical trees, dendritic trees are strongly tapered towards their tips. This tapering has previously been shown to offer a number of advantages over a constant width, both in terms of reduced energy requirements and the robust integration of inputs at different locations. However, in order to predict the computations that neurons perform, analytical solutions for the flow of input currents tend to assume constant dendritic diameters. Here we introduce an asymptotic approximation that accurately models the current transfer in dendritic trees with arbitrary, continuously changing, diameters. When we then determine the diameter profiles that maximise current transfer towards the cell body we find diameters similar to those observed in real neurons. We conclude that the tapering in dendritic trees to optimise signal transmission is a fundamental architectural principle of the brain.
Dieser Bericht stellt die wesentlichen Ergebnisse der sozialwissenschaftlichen und ökologischen Begleitforschung in der Modellregion Elektromobilität Rhein-Main (SÖB) dar. Dabei wird zunächst das Projektumfeld vorgestellt, indem auf die Rahmenbedingungen des Förderprogramms sowie weitere Programme und Projekte im Bereich Elektromobilität eingegangen wird. Im zweiten Kapitel wird das Projektkonsortium und dessen Einbettung in die Modellregion Rhein-Main erläutert, sowie die Verknüpfung mit der überregionalen Begleitforschung der Nationalen Organisation Wasser- und Brennstoffzellentechnologie (NOW). Im Kapitel 3 wird das Forschungsdesign der SÖB skizziert. Dazu werden einige Erkenntnisse aus der ersten Förderperiode beleuchtet, die für die Forschungsziele der aktuellen Förderperiode ausschlaggebend waren. Des Weiteren erfolgt eine Ausführung der methodischen Vorgehensweisen der Projektpartner. Das darauf folgende Kapitel 4 stellt die wesentlichen Ergebnisse des Projekts dar. Dabei wurde bewusst versucht, die verschie¬denen Erkenntnisse der einzelnen Partner thematisch miteinander zu verknüpfen. Aus den Ergeb¬nissen wurden Handlungsempfehlungen für verschiedene Bereiche und Akteure generiert, die in Kapitel 5 einfließen. Abschließend rundet ein Fazit mit zusammenfassenden Erkenntnissen den Bericht ab.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.