Dynamics, stratospheric ozone, and climate change

Dynamics affects the distribution and abundance of stratospheric ozone directly through transport of ozone itself and indirectly through its effect on ozone chemistry via temperature and transport of other chemical species. Dynamical processes must be considered in order to understand past ozone changes, especially in the northern hemisphere where there appears to be significant low-frequency variability which can look “trend-like” on decadal time scales. A major challenge is to quantify the predictable, or deterministic, component of past ozone changes. Over the coming century, changes in climate will affect the expected recovery of ozone. For policy reasons it is important to be able to distinguish and separately attribute the effects of ozone-depleting substances and greenhouse gases on both ozone and climate. While the radiative-chemical effects can be relatively easily identified, this is not so evident for dynamics — yet dynamical changes (e.g., changes in the Brewer-Dobson circulation) could have a first-order effect on ozone over particular regions. Understanding the predictability and robustness of such dynamical changes represents another major challenge. Chemistry-climate models have recently emerged as useful tools for addressing these questions, as they provide a self-consistent representation of dynamical aspects of climate and their coupling to ozone chemistry. We can expect such models to play an increasingly central role in the study of ozone and climate in the future, analogous to the central role of global climate models in the study of tropospheric climate change

Online Stakeholder Interactions in the Early Stage of a Megaproject

The purpose of this paper is to examine the network structure of online stakeholder discussions in the planning stage of a UK public mega project, High Speed Rail. By providing new rail connections between London, Birmingham and Manchester, this project is highly complex as it is embedded in a network of stakeholder relationships that may support or oppose the project. Data drawn from Twitter was analyzed using Social Network Analysis and inductive analysis of user profiles and content. Findings indicate that the majority of online stakeholders oppose the project and form stable clusters. Larger clusters within this network may attempt to deploy power directly in the form of a manipulation strategy while smaller clusters may seek to ally themselves with more powerful groups, a pathway strategy. Overall, the methodology is a useful complement to existing methods and may provide real time insights into the complex, evolving discussions around mega projects

Causes of maladaptation

Evolutionary biologists tend to approach the study of the natural world within a framework of adaptation, inspired perhaps by the power of natural selection to produce fitness advantages that drive population persistence and biological diversity. In contrast, evolution has rarely been studied through the lens of adaptation's complement, maladaptation. This contrast is surprising because maladaptation is a prevalent feature of evolution: population trait values are rarely distributed optimally; local populations often have lower fitness than imported ones; populations decline; and local and global extinctions are common. Yet we lack a general framework for understanding maladaptation; for instance in terms of distribution, severity, and dynamics. Similar uncertainties apply to the causes of maladaptation. We suggest that incorporating maladaptation-based perspectives into evolutionary biology would facilitate better understanding of the natural world. Approaches within a maladaptation framework might be especially profitable in applied evolution contexts – where reductions in fitness are common. Toward advancing a more balanced study of evolution, here we present a conceptual framework describing causes of maladaptation. As the introductory article for a Special Feature on maladaptation, we also summarize the studies in this Issue, highlighting the causes of maladaptation in each study. We hope that our framework and the papers in this Special Issue will help catalyze the study of maladaptation in applied evolution, supporting greater understanding of evolutionary dynamics in our rapidly changing world

A delicate balance between antibody evasion and ACE2 affinity for Omicron BA.2.75

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have caused successive global waves of infection. These variants, with multiple mutations in the spike protein, are thought to facilitate escape from natural and vaccine-induced immunity and often increase in affinity for ACE2. The latest variant to cause concern is BA.2.75, identified in India where it is now the dominant strain, with evidence of wider dissemination. BA.2.75 is derived from BA.2 and contains four additional mutations in the receptor-binding domain (RBD). Here, we perform an antigenic and biophysical characterization of BA.2.75, revealing an interesting balance between humoral evasion and ACE2 receptor affinity. ACE2 affinity for BA.2.75 is increased 9-fold compared with BA.2; there is also evidence of escape of BA.2.75 from immune serum, particularly that induced by Delta infection, which may explain the rapid spread in India, where where there is a high background of Delta infection. ACE2 affinity appears to be prioritized over greater escape

Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

Dijet production in √s = 7 TeV pp collisions with large rapidity gaps at the ATLAS experiment

A 6.8 nb−¹ sample of pp collision data collected under low-luminosity conditions at √s = 7 TeV by the ATLAS detector at the Large Hadron Collider is used to study diffractive dijet production. Events containing at least two jets with pT > 20 GeV are selected and analysed in terms of variables which discriminate between diffractive and non-diffractive processes. Cross sections are measured differentially in ΔηF, the size of the observable forward region of pseudorapidity which is devoid of hadronic activity, and in an estimator, ξ˜, of the fractional momentum loss of the proton assuming single diffractive dissociation (pp → p X). Model comparisons indicate a dominant non-diffractive contribution up to moderately large ηF and small ξ˜, with a diffractive contribution which is significant at the highest ΔηF and the lowest ξ˜. The rapidity-gap survival probability is estimated from comparisons of the data in this latter region with predictions based on diffractive parton distribution functions

Search for strong gravity in multijet final states produced in pp collisions at √s=13 TeV using the ATLAS detector at the LHC

A search is conducted for new physics in multijet final states using 3.6 inverse femtobarns of data from proton-proton collisions at √s = 13TeV taken at the CERN Large Hadron Collider with the ATLAS detector. Events are selected containing at least three jets with scalar sum of jet transverse momenta (HT) greater than 1TeV. No excess is seen at large HT and limits are presented on new physics: models which produce final states containing at least three jets and having cross sections larger than 1.6 fb with HT > 5.8 TeV are excluded. Limits are also given in terms of new physics models of strong gravity that hypothesize additional space-time dimensions

Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at sqrt [ s ] = 13TeV

A search for physics beyond the Standard Model, in final states with at least one high transverse momentum charged lepton (electron or muon) and two additional high transverse momentum leptons or jets, is performed using 3.2 fb−1 of proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015 at √s = 13 TeV. The upper end of the distribution of the scalar sum of the transverse momenta of leptons and jets is sensitive to the production of high-mass objects. No excess of events beyond Standard Model predictions is observed. Exclusion limits are set for models of microscopic black holes with two to six extra dimensions