Exploring vague language use and voice variation in human-agent interaction

This thesis addresses the linguistic phenomenon of vague language (VL) and its effect on the creation of identity in the emerging and developing field of human-agent interaction (HAI). Current research on VL has focused on human interaction, while similar existing literature on language in HAI has focused on politeness theory and facework. This thesis brings the two research fields together and uses them as a focusing lens to investigate the issue of identity in agents – software with varying degrees of autonomy and intelligence. Agents are increasingly common in our everyday lives, particularly in the role of an instructor. Intelligent personal assistants are a frequent feature on smartphones, automated checkout systems pervade supermarkets both large and small, and satellite navigation systems have been a mainstay for over a decade now. Despite their frequency, there is relatively little research into the communication challenges surrounding HAI. Much like other people, the language and voice of agents have the ability to affect our perceptions and of them, and shape the way in which we create their identities. Instruction giving, amongst other facets of talk, in human communication can be mitigated through the use of VL. This can reduce the imposition we have on interaction partners, pay respect to a listener’s face, and establish and maintain a positive rapport with our interlocutors. This can have a profound effect on the desire to interact with someone again. Furthermore, agents that use speech to communicate are assigned one of two varieties of voice – synthesised or pre-recorded human speech, both of which have documented benefits and drawbacks. Given the rise of agents in the modern world, it is in the best interest of all parties to understand the salient variables that affect our perceptions of agents, and what effect VL and other variables such as voice in language and voice may have in our interactions with them. This thesis provides a novel approach to investigating both VL and voice in HAI. A general framework is presented with the use of a specific VL model to apply in the interactions, which is designed around verbal agents giving people instructions on how to construct Lego models. The first study compares the effects of a vague and non-vague verbal agent in this context, while the second study focuses on the comparative use of synthesised text-to-speech voices and professional human recordings in the same context. The results from the investigation reveal key findings regarding the use of VL in a verbal agent instructive context. The first study indicated that a synthesised agent voice is better suited to using non-vague instructions, while the second study revealed that a professional voice actor is a preferable candidate for using VL in comparison to two different synthesised voices. These findings discuss the issue of identities in HAI. They reveal that, when an agent instructor is perceived to have a voice that is non-human and machinelike, it is more likely that its use of VL will be received less positively. This is often because the combination of voice and language do not mix, but is also a result of a clash of perceived group identities between agent and human speech. As agents are typically direct, the use of “humanlike” VL can create a large disparity between a person’s expectations of agent speech and the reality of the interaction. Similarly, if an agent’s voice has more of a humanlike feel to it, then its use of VL will create less disparity and has the potential to bridge the gap between these two group identities. This poses discussions on the nature of agent identity and how it compares to those in humans. The thesis concludes with reflection on the findings in light of existing linguistic theories, and how further research into this field may assist agent designers, researchers, and agent users alike. A suggestion of employing a corpus linguistics approach to HAI is proposed, which may pave the way for future success in this area

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The ATLAS trigger system for LHC Run 3 and trigger performance in 2022

The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025)

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 diferent 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 √s = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, tt¯, and tb) or third-generation leptons (τν and τ τ ) are included in this kind of combination for the frst time. A simplifed model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confdence 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

Searches for exclusive Higgs boson decays into D⁎γ and Z boson decays into D0γ and Ks0γ in pp collisions at √s = 13 TeV with the ATLAS detector

Searches for exclusive decays of the Higgs boson into D⁎γ and of the Z boson into D0γ and Ks0γ can probe flavour-violating Higgs boson and Z boson couplings to light quarks. Searches for these decays are performed with a pp collision data sample corresponding to an integrated luminosity of 136.3 fb−1 collected at s=13TeV between 2016–2018 with the ATLAS detector at the CERN Large Hadron Collider. In the D⁎γ and D0γ channels, the observed (expected) 95% confidence-level upper limits on the respective branching fractions are B(H→D⁎γ)<1.0(1.2)×10−3, B(Z→D0γ)<4.0(3.4)×10−6, while the corresponding results in the Ks0γ channel are B(Z→Ks0γ)<3.1(3.0)×10−6

Measurement of vector boson production cross sections and their ratios using pp collisions at √s = 13.6 TeV with the ATLAS detector

Abstract available from publisher's website

Beam-induced backgrounds measured in the ATLAS detector during local gas injection into the LHC beam vacuum

Inelastic beam-gas collisions at the Large Hadron Collider (LHC), within a few hundred metres of the ATLAS experiment, are known to give the dominant contribution to beam backgrounds. These are monitored by ATLAS with a dedicated Beam Conditions Monitor (BCM) and with the rate of fake jets in the calorimeters. These two methods are complementary since the BCM probes backgrounds just around the beam pipe while fake jets are observed at radii of up to several metres. In order to quantify the correlation between the residual gas density in the LHC beam vacuum and the experimental backgrounds recorded by ATLAS, several dedicated tests were performed during LHC Run 2. Local pressure bumps, with a gas density several orders of magnitude higher than during normal operation, were introduced at different locations. The changes of beam-related backgrounds, seen in ATLAS, are correlated with the local pressure variation. In addition the rates of beam-gas events are estimated from the pressure measurements and pressure bump profiles obtained from calculations. Using these rates, the efficiency of the ATLAS beam background monitors to detect beam-gas events is derived as a function of distance from the interaction point. These efficiencies and characteristic distributions of fake jets from the beam backgrounds are found to be in good agreement with results of beam-gas simulations performed with theFluka Monte Carlo programme

Measurement of ZZ production cross-sections in the four-lepton final state in pp collisions at √s = 13.6 TeV with the ATLAS experiment

This paper reports cross-section measurements of ZZ production in pp collisions at √s = 13.6TeV at the Large Hadron Collider. The data were collected by the ATLAS detector in 2022, and correspond to an integrated luminosity of 29 fb−1. Events in the ZZ → 4ℓ (ℓ = e, μ) final states are selected and used to measure the inclusive and differential cross-sections in a fiducial region defined close to the analysis selections. The inclusive cross-section is further extrapolated to the total phase space with a requirement of 66 <mZ < 116 GeV for both Z bosons, yielding 16.8 ± 1.1 pb. The results are well described by the Standard Model predictions

Measurement of the tt¯ cross section and its ratio to the Z production cross section using pp collisions at √s = 13.6 TeV with the ATLAS detector

The inclusive top-quark-pair production cross section σtt¯ and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at √s = 13.6 TeV, using 29 fb−1 of data collected in 2022 with the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge electron-muon pair and b-tagged jets, and assuming Standard Model decays, the top-quark-pair production cross section is measured to be σtt¯=850±3(stat.)±18(syst.)±20(lumi.) pb. The ratio of the tt¯ and the Z-boson production cross sections is also measured, where the Z-boson contribution is determined for inclusive e+e− and μ+μ− events in a fiducial phase space. The relative uncertainty on the ratio is reduced compared to the tt¯ cross section, thanks to the cancellation of several systematic uncertainties. The result for the ratio, Rtt¯/Z=1.145±0.003(stat.)±0.021(syst.)±0.002(lumi.) is consistent with the Standard Model prediction using the PDF4LHC21 PDF set

Search for the Zγ decay mode of new high-mass resonances in pp collisions at √s = 13 TeV with the ATLAS detector

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The √s = 13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV