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An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures. Related Article: Erwann Grenet, Raphaël Robidas, Arie van der Lee, Claude Y. Legault, Xavier J. Salom‐Roig|2022|Eur.J.Org.Chem.|2022|e202200828|doi:10.1002/ejoc.202200828

C_N^sub(eta_1, eta_2) for Pb+Pb, pT>0.2GeV, (160<=Nch<180) No data abstract available.

Related Article: Michelle B. Mills, Carolyn A. Michalowicz, Ellen Song, Adam C. Maahs, Julia A. Newman, Taylr Cawte, Jessica M. Lovnicki, Dmitriy V. Soldatov, Kathryn E. Preuss|2021|Cryst.Growth Des.|21|5897|doi:10.1021/acs.cgd.1c00791

Fig 2 (heatmap) data files and R codeData and R code needed to create Fig 2 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 figure panels. Each file contains evolved D across the range in each of 500 generations of stable climate followed by 1000 generations of climate change.Fig 2 (heatmap).zipFig 3 (D lines) data and R codeData and R code needed to create Fig 3 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 models shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, averaged across 10 runs per cost per model.Fig 3 (D lines).zipFig 4 (delta.D) data and R codeData and R code needed to create Fig 4 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 4 models (ie figure rows) shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change for 30 runs per model.Fig 4 (delta.D).zipFig 6 (D vs density) data and R codeData and R code needed to create Fig 6 in Hargreaves et al (2015) J Evol Biol. Two data files (one for evolved D and one for density) for each of 2 model runs, one with dispersal (dispersal distance =1 as normal) and one run without dispersal (dispersal distance =0).Fig 6 (D vs density).zipAppendix S1 data and R code for each figureData and R code needed to create figures in Appendix S1 in Hargreaves et al (2015) J Evol Biol. All figures remake Fig 3 while varying one parameter. Fig S1.1 shows murate = .005; Fig S1.2 shows avshift = .01, .05, .2; Fig. S1.3 shows K=10; Fig. S1.4 shows effect of eliminating kin selection by randomizing individuals within columns before each dispersal event. For each figure there is 1 data file per model. Each data file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, for 10 runs per cost.Appendix S1.zipModel code Matlab fileCode to run the model simulations.rangeshift (for dryad).mFig 5 (extinction threshold) Matlab codeMatlab code to run the simulations necessary to determine the relationship between the speed of climate change (avshift) and probability of extinction.rangeshift_thresh (for dryad).m Dispersal ability will largely determine whether species track their climatic niches during climate change, a process especially important for populations at contracting (low-latitude/low-elevation) range limits that otherwise risk extinction. We investigate whether dispersal evolution at contracting range limits is facilitated by two processes that potentially enable edge populations to experience and adjust to the effects of climate deterioration before they cause extinction: (i) climate-induced fitness declines towards range limits and (ii) local adaptation to a shifting climate gradient. We simulate a species distributed continuously along a temperature gradient using a spatially explicit, individual-based model. We compare range-wide dispersal evolution during climate stability vs. directional climate change, with uniform fitness vs. fitness that declines towards range limits (RLs), and for a single climate genotype vs. multiple genotypes locally adapted to temperature. During climate stability, dispersal decreased towards RLs when fitness was uniform, but increased when fitness declined towards RLs, due to highly dispersive genotypes maintaining sink populations at RLs, increased kin selection in smaller populations, and an emergent fitness asymmetry that favoured dispersal in low-quality habitat. However, this initial dispersal advantage at low-fitness RLs did not facilitate climate tracking, as it was outweighed by an increased probability of extinction. Locally adapted genotypes benefited from staying close to their climate optima; this selected against dispersal under stable climates but for increased dispersal throughout shifting ranges, compared to cases without local adaptation. Dispersal increased at expanding RLs in most scenarios, but only increased at the range centre and contracting RLs given local adaptation to climate.

Centre of mass absolute differential cross sections at pion kinetic energy 141.15 MeV using the liquid H2 target and two arm pion detection. There is an additional systematic error of 1.3 PCT (1.6 PCT) for PI+ (PI-) beams which is not included in the errors shown in the table. TRIUMF. Precision measurement of the pion-proton elastic differential crosssections at incident pion kinetic energy from 141.15 to 267.3 GeV. The experiment uses a supercooled liquid hydrogen target as well as a solid CH2 target.

CERN-LHC. A search for electroweak production of supersymmetric particles is performed in two-lepton and three-lepton final states using recursive jigsaw reconstruction. The search uses data collected in 2015 and 2016 by the ATLAS experiment in $\sqrt{s}$ = 13 TeV proton--proton collisions at the CERN Large Hadron Collider corresponding to an integrated luminosity of 36.1 $\textrm{fb}^{-1}$. Chargino--neutralino pair production, with decays via $W/Z$ bosons, is studied in final states involving leptons and jets and missing transverse momentum for scenarios with large and intermediate mass-splittings between the parent particle and lightest supersymmetric particle, as well as for the scenario where this mass splitting is close to the mass of the $Z$ boson. The latter case is challenging since the vector bosons are produced with kinematic properties that are similar to those in Standard Model processes. Results are found to be compatible with the Standard Model expectations in the signal regions targeting large and intermediate mass-splittings, and chargino--neutralino masses up to 600 GeV are excluded at 95% confidence level for a massless lightest supersymmetric particle. Excesses of data above the expected background are found in the signal regions targeting low mass-splittings, and the largest local excess amounts to 3.0 standard deviations. Distributions of kinematic variables in the signal regions for the $2\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution for $R_{\textrm{ISR}}$ in SR$2\ell$_ISR is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Measurements of the top--antitop quark pair production charge asymmetry in the dilepton channel are presented using data corresponding to an integrated luminosity of 20.3 $fb^{-1}$ from pp collisions at a center-of-mass energy of $\sqrt{s}=8\,$ TeV collected with the ATLAS detector at the Large Hadron Collider at CERN. Inclusive and differential measurements as a function of the invariant mass, transverse momentum, and longitudinal boost of the $t\bar{t}$ system are performed both in the full phase space and in a fiducial phase space closely matching the detector acceptance. Two observables are studied: $A_{ll}^{C}$ based on the selected leptons and $A_{t\bar{t}}^C$ based on the reconstructed $t\bar{t}$ final state. The inclusive asymmetries are measured in the full phase space to be $A_{ll}^{C} =0.008 \pm 0.006$ and $A_{t\bar{t}}^C = 0.021 \pm 0.016$, which are in agreement with the Standard Model predictions of $A_{ll}^{C} = 0.0064 \pm 0.0003$ and $A_{t\bar{t}}^C = 0.0111 \pm 0.0004$. The top-antitop inclusive asymmetry in the fiducial volume.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures. Related Article: Laureline Lecarme, Linus Chiang, Jules Moutet, Nicolas Leconte, Christian Philouze, Olivier Jarjayes, Tim Storr, Fabrice Thomas|2016|Dalton Trans.|45|16325|doi:10.1039/C6DT02163H

SRC for p+Pb, pT>0.2GeV, opposite pairs No data abstract available.