Effect of Growth Temperature on Bamboo-shaped Carbon–Nitrogen (C–N) Nanotubes Synthesized Using Ferrocene Acetonitrile Precursor

This investigation deals with the effect of growth temperature on the microstructure, nitrogen content, and crystallinity of C–N nanotubes. The X-ray photoelectron spectroscopic (XPS) study reveals that the atomic percentage of nitrogen content in nanotubes decreases with an increase in growth temperature. Transmission electron microscopic investigations indicate that the bamboo compartment distance increases with an increase in growth temperature. The diameter of the nanotubes also increases with increasing growth temperature. Raman modes sharpen while the normalized intensity of the defect mode decreases almost linearly with increasing growth temperature. These changes are attributed to the reduction of defect concentration due to an increase in crystal planar domain sizes in graphite sheets with increasing temperature. Both XPS and Raman spectral observations indicate that the C–N nanotubes grown at lower temperatures possess higher degree of disorder and higher N incorporation

Nucleo-cytoplasmic transport of proteins and RNA in plants

Merkle T. Nucleo-cytoplasmic transport of proteins and RNA in plants. Plant Cell Reports. 2011;30(2):153-176.Transport of macromolecules between the nucleus and the cytoplasm is an essential necessity in eukaryotic cells, since the nuclear envelope separates transcription from translation. In the past few years, an increasing number of components of the plant nuclear transport machinery have been characterised. This progress, although far from being completed, confirmed that the general characteristics of nuclear transport are conserved between plants and other organisms. However, plant-specific components were also identified. Interestingly, several mutants in genes encoding components of the plant nuclear transport machinery were investigated, revealing differential sensitivity of plant-specific pathways to impaired nuclear transport. These findings attracted attention towards plant-specific cargoes that are transported over the nuclear envelope, unravelling connections between nuclear transport and components of signalling and developmental pathways. The current state of research in plants is summarised in comparison to yeast and vertebrate systems, and special emphasis is given to plant nuclear transport mutants

Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at s = 13 TeV with the ATLAS detector

This paper presents the measurement of fducial and diferential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity diference. The measured fducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.)fb and 3.38±0.22 (stat.)±0.19 (syst.)fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confdence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global signifcance of 2.5 standard deviations

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p