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Institute
The minimum-bias multiplicity distribution and the transverse momentum and pseudorapidity distributions for central collisions have been measured for negative hadrons ( h-) in Au+Au interactions at sqrt[sNN] = 130 GeV. The multiplicity density at midrapidity for the 5% most central interactions is dNh-/d eta | eta = 0 = 280±1(stat)±20(syst), an increase per participant of 38% relative to pp-bar collisions at the same energy. The mean transverse momentum is 0.508±0.012 GeV/c and is larger than in central Pb+Pb collisions at lower energies. The scaling of the h- yield per participant is a strong function of pperp. The pseudorapidity distribution is almost constant within | eta |<1.
The production of the Λ(1520) baryonic resonance has been measured at midrapidity in inelastic pp collisions at s√=7 TeV and in p–Pb collisions at sNN−−−√=5.02 TeV for non-single diffractive events and in multiplicity classes. The resonance is reconstructed through its hadronic decay channel Λ(1520) →pK− and the charge conjugate with the ALICE detector. The integrated yields and mean transverse momenta are calculated from the measured transverse momentum distributions in pp and p–Pb collisions. The mean transverse momenta follow mass ordering as previously observed for other hyperons in the same collision systems. A Blast-Wave function constrained by other light hadrons (π, K, K0S, p, Λ) describes the shape of the Λ(1520) transverse momentum distribution up to 3.5 GeV/c in p–Pb collisions. In the framework of this model, this observation suggests that the Λ(1520) resonance participates in the same collective radial flow as other light hadrons. The ratio of the yield of Λ(1520) to the yield of the ground state particle Λ remains constant as a function of charged-particle multiplicity, suggesting that there is no net effect of the hadronic phase in p–Pb collisions on the Λ(1520) yield.
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.