THE SOLAR WIND AS A POSSIBLE SOURCE OF FAST TEMPORAL VARIATIONS OF THE HELIOSPHERIC RIBBON

We present a possible source of pickup ions (PUIs) the ribbon observed by the Interstellar Boundary EXplorer (IBEX). We suggest that a gyrating solar wind and PUIs in the ramp and in the near downstream region of the termination shock (TS) could provide a significant source of energetic neutral atoms (ENAs) in the ribbon. A fraction of the solar wind and PUIs are reflected and energized during the first contact with the TS. Some of the solar wind may be reflected propagating toward the Sun but most of the solar wind ions form a gyrating beam-like distribution that persists until it is fully thermalized further downstream. Depending on the strength of the shock, these gyrating distributions can exist for many gyration periods until they are scattered/thermalized due to wave-particle interactions at the TS and downstream in the heliosheath. During this time, ENAs can be produced by charge exchange of interstellar neutral atoms with the gyrating ions. In order to determine the flux of energetic ions, we estimate the solar wind flux at the TS using pressure estimates inferred from in situ measurements. Assuming an average path length in the radial direction of the order of a few AU before the distribution of gyrating ions is thermalized, one can explain a significant fraction of the intensity of ENAs in the ribbon observed by IBEX. With a localized source and such a short integration path, this model would also allow fast time variations of the ENA flux.

Measurement of the Azimuthal Angle Dependence of Inclusive Jet Yields in Pb+Pb Collisions at sqrts_NN= 2.76 TeV with the ATLAS detector

Measurements of the variation of inclusive jet suppression as a function of relative azimuthal angle, Delta phi, with respect to the elliptic event plane provide insight into the path-length dependence of jet quenching. ATLAS has measured the Delta phi dependence of jet yields in 0.14 nb(-1) of root s(NN) = 2.76 TeV Pb + Pb collisions at the LHC for jet transverse momenta p(T) > 45 GeV in different collision centrality bins using an underlying event subtraction procedure that accounts for elliptic flow. The variation of the jet yield with Delta phi was characterized by the parameter, nu(jet)(2), and the ratio of out-of-plane (Delta phi similar to pi/2) to in-plane (Delta phi similar to 0) yields. Nonzero nu(jet)(2) values were measured in all centrality bins for p(T) < 160 GeV. The jet yields are observed to vary by as much as 20% between in-plane and out-of-plane directions.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

A Comprehensive Discussion of HMBC Pulse Sequences: 4. Establishing Two-Bond Correlations from HMBC and Related Experiments

The utility of the HMBC experiment for structure elucidation is unquestionable, but the nature of the coupling pathways leading to correlations in an HMBC experiment creates the potential for misinterpretation. This misinterpretation potential is intimately linked to the size of the long-range heteronuclear couplings involved, and may become troublesome in those cases of a particularly strong 2JCH correlation that might be mistaken for a 3JCH correlation or a 4JCH correlation of appreciable strength that could be mistaken for a weaker 3JCH correlation. To address these potential avenues of confusion, work from several laboratories has been focused on the development of what might be considered “coupling pathway edited” long-range heteronuclear correlation experiments that are derived from or related to the HMBC experiment. The first example of an effort to address the problems associated with correlation path length was seen in the heteronucleus-detected XCORFE experiment described by Reynolds and co-workers that predated the development of the HMBC experiment. Proton-detected analogs of the HMBC experiment intended to differentiate 2JCH correlations from nJCH correlations where n = 3, 4, include the 2J,3J-HMBC, HMBC-RELAY, H2BC, edited-HMBC, and HAT H2BC experiments. The principles underlying the critical components of each of these experiments are discussed and experimental verification of the results that can be obtained using model compounds are shown. This contribution concludes with a brief discussion of the 1,1-ADEQUATE experiments that provide an alternative means of identifying adjacent protonated and non-protonated carbon correlations by exploiting 1JCC correlations at natural abundance.