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The ALICE collaboration at the CERN LHC reports novel measurements of jet substructure in pp collisions at s√= 7 TeV and central Pb-Pb collisions at sNN−−−√ = 2.76 TeV. Jet substructure of track-based jets is explored via iterative declustering and grooming techniques. We present the measurement of the momentum sharing of two-prong substructure exposed via grooming, the zg, and its dependence on the opening angle, in both pp and Pb-Pb collisions. We also present the first measurement of the distribution of the number of branches obtained in the iterative declustering of the jet, which is interpreted as the number of its hard splittings. In Pb-Pb collisions, we observe a suppression of symmetric splittings at large opening angles and an enhancement of splittings at small opening angles relative to pp collisions, with no significant modification of the number of splittings. The results are compared to predictions from various Monte Carlo event generators to test the role of important concepts in the evolution of the jet in the medium such as color coherence.
The elliptic flow (v2) of (anti-)3He is measured in Pb–Pb collisions at √sNN=5.02TeV in the transverse-momentum (pT) range of 2–6 GeV/c for the centrality classes 0–20%, 20–40%, and 40–60% using the event-plane method. This measurement is compared to that of pions, kaons, and protons at the same center-of-mass energy. A clear mass ordering is observed at low pT, as expected from relativistic hydrodynamics. The violation of the scaling of v2 with the number of constituent quarks at low pT, already observed for identified hadrons and deuterons at LHC energies, is confirmed also for (anti-)3He. The elliptic flow of (anti-)3He is underestimated by the Blast-Wave model and overestimated by a simple coalescence approach based on nucleon scaling. The elliptic flow of (anti-)3He measured in the centrality classes 0–20% and 20–40% is well described by a more sophisticated coalescence model where the phase-space distributions of protons and neutrons are generated using the iEBE-VISHNU hybrid model with AMPT initial conditions.
A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012 are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations, and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO dataset is archived monthly from 2001–2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less, and found to be less than 30 % for almost all cases. The trajectory-mapped CO dataset has also been validated by comparison profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %.
Maps are also compared with Version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. While agreement is good in the lowermost troposphere, the MOPITT CO profile shows negative biases of ∼ 20 % between 500 and 300 hPa. These upper troposphere biases are not related to the
mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS climatology column agrees with the MOPITT CO total column within ±5 %, which is consistent with previous reports.
The maps clearly show major regional CO sources such as biomass burning in the central and southern Africa and anthropogenic emissions in eastern China. The dataset shows the seasonal CO cycle over different latitude bands and altitude ranges that are representative of the regions as well as long-term trends over latitude bands. We observe a decline in CO over the Northern Hemisphere extratropics and the tropics consistent with that reported by previous studies.
Similar maps have been made using the concurrent O3 measurements by MOZAICIAGOS, as the global variation of O3–CO correlations can be a useful tool for the evaluation of ozone sources and transport in chemical transport models. We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO dataset as an a priori climatology for satellite retrieval, and for air quality model validation and initialization.
A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012, are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO data set is archived monthly from 2001 to 2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, firstly by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less and found to be less than 30 % for almost all cases. Secondly, the method has been validated by comparing profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %. Finally, the mapping product is compared with global MOZAIC-IAGOS cruise-level data, which were not included in the trajectory-mapped data set, and with independent data from the NOAA aircraft flask sampling program. The trajectory-mapped MOZAIC-IAGOS CO values show generally good agreement with both independent data sets.
Maps are also compared with version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. Both data sets clearly show major regional CO sources such as biomass burning in Central and southern Africa and anthropogenic emissions in eastern China. While the maps show similar features and patterns, and relative biases are small in the lowermost troposphere, we find differences of ∼ 20 % in CO volume mixing ratios between 500 and 300 hPa. These upper-tropospheric biases are not related to the mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS column is also higher than the MOPITT CO total column by 12–16 %.
The data set shows the seasonal CO cycle over different latitude bands and altitude ranges as well as long-term trends over different latitude bands. We observe a decline in CO over the northern hemispheric extratropics and the tropics consistent with that reported by previous studies using other data sources.
We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO data set as an a priori climatology for satellite retrieval and for air quality model validation and initialization.
Members of the genus Xenorhabdus are entomopathogenic bacteria that associate with nematodes. The nematode-bacteria pair infects and kills insects, with both partners contributing to insect pathogenesis and the bacteria providing nutrition to the nematode from available insect-derived nutrients. The nematode provides the bacteria with protection from predators, access to nutrients, and a mechanism of dispersal. Members of the bacterial genus Photorhabdus also associate with nematodes to kill insects, and both genera of bacteria provide similar services to their different nematode hosts through unique physiological and metabolic mechanisms. We posited that these differences would be reflected in their respective genomes. To test this, we sequenced to completion the genomes of Xenorhabdus nematophila ATCC 19061 and Xenorhabdus bovienii SS-2004. As expected, both Xenorhabdus genomes encode many anti-insecticidal compounds, commensurate with their entomopathogenic lifestyle. Despite the similarities in lifestyle between Xenorhabdus and Photorhabdus bacteria, a comparative analysis of the Xenorhabdus, Photorhabdus luminescens, and P. asymbiotica genomes suggests genomic divergence. These findings indicate that evolutionary changes shaped by symbiotic interactions can follow different routes to achieve similar end points.
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
The procedure for the energy calibration of the high granularity electromagnetic calorimeter PHOS of the ALICE experiment is presented. The methods used to perform the relative gain calibration, to evaluate the geometrical alignment and the corresponding correction of the absolute energy scale, to obtain the nonlinearity correction coefficients and finally, to calculate the time-dependent calibration corrections, are discussed and illustrated by the PHOS performance in proton-proton (pp) collisions at √s=13 TeV. After applying all corrections, the achieved mass resolutions for π0 and η mesons for pT > 1.7 GeV/c are σmπ0 = 4.56 ± 0.03 MeV/c2 and σmη = 15.3 ± 1.0 MeV/c2, respectively.
The procedure for the energy calibration of the high granularity electromagnetic calorimeter PHOS of the ALICE experiment is presented. The methods used to perform the relative gain calibration, to evaluate the geometrical alignment and the corresponding correction of the absolute energy scale, to obtain the nonlinearity correction coefficients and finally, to calculate the time-dependent calibration corrections, are discussed and illustrated by the PHOS performance in proton-proton (pp) collisions at s√=13 TeV. After applying all corrections, the achieved mass resolution of π0 and η mesons for pT>1.7 GeV/c is σπ0m=4.56±0.03 MeV/c2 and σηm=15.3±1.0 MeV/c2.
The procedure for the energy calibration of the high granularity electromagnetic calorimeter PHOS of the ALICE experiment is presented. The methods used to perform the relative gain calibration, to evaluate the geometrical alignment and the corresponding correction of the absolute energy scale, to obtain the nonlinearity correction coefficients and finally, to calculate the time-dependent calibration corrections, are discussed and illustrated by the PHOS performance in proton-proton (pp) collisions at s√ = 13 TeV. After applying all corrections, the achieved mass resolutions for π0 and η mesons for pT>1.7 GeV/c are σπ0m=4.56±0.03 MeV/c2 and σηm=15.3±1.0 MeV/c2, respectively.