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Studies show that young autistic adults are under- or unemployed, with almost half never holding a paying job in their 20’s. Unemployment within this population leads to decreased personal growth and increased dependence on caregivers. Research suggests that the interview process is one of the largest barriers to employment for this population. Autistic individuals often struggle with emotion regulation, which can be exacerbated by the interview process. To address this, we propose the use of a stress detection model in conjunction with a virtual reality interview simulator. This combination will allow for the interview to adapt to the state of the participant to improve the skills and engagement of the user and positively influence their comfort level. Data regarding negative affective responses to categories of questions can also be used to inform employers on better interviewing techniques. A model was designed using data obtained from neurotypical participants completing a modified Computerized Paced Serial Addition Task (PASAT-C) and evaluated on a dataset obtained from Autistic participants who took part in a simulated interview. Agreement between the model and ground truth was compared based on Pearson correlation coefficients. It was found that was r(289) = 0.28, which was statistically significant (p < .001; CI: 0.17 to 0.38). Our preliminary results provide evidence for the validity of observer-based labeling of data captured using a wrist-worn physiological sensor. 

Employment of autistic individuals is strikingly low in relation to the skill level and capabilities of this population. Roughly 65% of autistic adults are either unemployed or underemployed relative to their abilities but there is increasing recognition that this number could be greatly improved through empowering autistic individuals while simultaneously providing a boost to the economy. Much of this disparity can be attributed in part to the lack of awareness and understanding among employers regarding behavior of autistic individuals during the hiring process. Most notably, the job interview—where strong eye contact is traditionally expected but can be extremely uncomfortable for autistic individuals—presents an unreasonable initial barrier to employment for many. The current work presents a data visualization dashboard that is populated with quantitative data (including eye tracking data) captured during simulated job interviews using a novel interview simulator called Career Interview Readiness in Virtual Reality (CIRVR). We conducted a brief series of case studies wherein autistic individuals who took part in a CIRVR interview and other key stakeholders provided lived experiences and qualitative insights into the most effective design and application of such data visualization dashboard. We conclude with a discussion of the role of information related to visual attention in job interviews with an emphasis on the importance of descriptive rather than prescriptive interpretation. 

The employment settings for autistic individuals in the USA is grim. As more children are diagnosed with ASD, the number of adolescent and young adult with ASD will increase as well over the next decade. Based on reports, one of the main challenges in securing and retaining employment for individual with ASD is difficulty in communicating and working with others in workplace settings. Most vocational trainings focused on technical skills development and very few addresses teamwork skills development. In this study, we present the design of a collaborative virtual environment (CVE) that support autistic individual to develop their teamwork skills by working together with a partner in a shared virtual space. This paper described the CVE architecture, teamwork-based tasks design and quantitative measures to evaluate teamwork skills. A system validation was also carried out to validate the system design. The results showed that our CVE was able to support multiple users in the same shared environment, the tasks were tolerable by users, and all the quantitative measures are recorded accordingly. 

The production of strange hadrons ($$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, Λ, Ξ^±, and Ω^±), baryon-to-meson ratios (Λ/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, Ξ/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, and Ω/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$), and baryon-to-baryon ratios (Ξ/Λ, Ω/Λ, and Ω/Ξ) associated with jets and the underlying event were measured as a function of transverse momentum (p_T) in pp collisions at$$ \sqrt{s} $$$\sqrt{s}$= 13 TeV and p Pb collisions at$$ \sqrt{s_{\textrm{NN}}} $$$\sqrt{s_{\mathrm{NN}}}$= 5.02 TeV with the ALICE detector at the LHC. The inclusive production of the same particle species and the corresponding ratios are also reported. The production of multi-strange hadrons, Ξ^±and Ω^±, and their associated particle ratios in jets and in the underlying event are measured for the first time. In both pp and p–Pb collisions, the baryon-to-meson and baryon-to-baryon yield ratios measured in jets differ from the inclusive particle production for low and intermediate hadronp_T(0.6–6 GeV/c). Ratios measured in the underlying event are in turn similar to those measured for inclusive particle production. In pp collisions, the particle production in jets is compared with Pythia8 predictions with three colour-reconnection implementation modes. None of them fully reproduces the data in the measured hadronp_Tregion. The maximum deviation is observed for Ξ^±and Ω^±which reaches a factor of about six. The event multiplicity dependence is further investigated in p−Pb collisions. In contrast to what is observed in the underlying event, there is no significant event-multiplicity dependence for particle production in jets. The presented measurements provide novel constraints on hadronisation and its Monte Carlo description. In particular, they demonstrate that the fragmentation of jets alone is insufficient to describe the strange and multi-strange particle production in hadronic collisions at LHC energies.

 

Abstract A newly developed observable for correlations between symmetry planes, which characterize the direction of the anisotropic emission of produced particles, is measured in Pb–Pb collisions at $$\sqrt{s_\text {NN}}$$ s NN  = 2.76 TeV with ALICE. This so-called Gaussian Estimator allows for the first time the study of these quantities without the influence of correlations between different flow amplitudes. The centrality dependence of various correlations between two, three and four symmetry planes is presented. The ordering of magnitude between these symmetry plane correlations is discussed and the results of the Gaussian Estimator are compared with measurements of previously used estimators. The results utilizing the new estimator lead to significantly smaller correlations than reported by studies using the Scalar Product method. Furthermore, the obtained symmetry plane correlations are compared to state-of-the-art hydrodynamic model calculations for the evolution of heavy-ion collisions. While the model predictions provide a qualitative description of the data, quantitative agreement is not always observed, particularly for correlators with significant non-linear response of the medium to initial state anisotropies of the collision system. As these results provide unique and independent information, their usage in future Bayesian analysis can further constrain our knowledge on the properties of the QCD matter produced in ultrarelativistic heavy-ion collisions. 

A study of multiplicity and pseudorapidity distributions of inclusive photons measured in pp and p–Pb collisions at a center-of-mass energy per nucleon–nucleon collision of$$\sqrt{s_{\textrm{NN}}}~=~5.02$$$\sqrt{s_{\text{NN}}}=5.02$ TeV using the ALICE detector in the forward pseudorapidity region 2.3 $$<~\eta _\textrm{lab} ~<$$$<{\eta }_{\text{lab}}<$ 3.9 is presented. Measurements in p–Pb collisions are reported for two beam configurations in which the directions of the proton and lead ion beam were reversed. The pseudorapidity distributions in p–Pb collisions are obtained for seven centrality classes which are defined based on different event activity estimators, i.e., the charged-particle multiplicity measured at midrapidity as well as the energy deposited in a calorimeter at beam rapidity. The inclusive photon multiplicity distributions for both pp and p–Pb collisions are described by double negative binomial distributions. The pseudorapidity distributions of inclusive photons are compared to those of charged particles at midrapidity in pp collisions and for different centrality classes in p–Pb collisions. The results are compared to predictions from various Monte Carlo event generators. None of the generators considered in this paper reproduces the inclusive photon multiplicity distributions in the reported multiplicity range. The pseudorapidity distributions are, however, better described by the same generators.

 

This article reports measurements of the angle between differently defined jet axes in pp collisions at$$ \sqrt{s} $$$\sqrt{s}$= 5.02 TeV carried out by the ALICE Collaboration. Charged particles at midrapidity are clustered into jets with resolution parametersR= 0.2 and 0.4. The jet axis, before and after Soft Drop grooming, is compared to the jet axis from the Winner-Takes-All (WTA) recombination scheme. The angle between these axes, ∆R_axis, probes a wide phase space of the jet formation and evolution, ranging from the initial high-momentum-transfer scattering to the hadronization process. The ∆R_axisobservable is presented for 20<$$ {p}_{\textrm{T}}^{\textrm{ch}\ \textrm{jet}} $$$p_T^{\mathrm{ch}\mathrm{jet}}$<100 GeV/c, and compared to predictions from the PYTHIA 8 and Herwig 7 event generators. The distributions can also be calculated analytically with a leading hadronization correction related to the non-perturbative component of the Collins-Soper-Sterman (CSS) evolution kernel. Comparisons to analytical predictions at next-to-leading-logarithmic accuracy with leading hadronization correction implemented from experimental extractions of the CSS kernel in Drell-Yan measurements are presented. The analytical predictions describe the measured data within 20% in the perturbative regime, with surprising agreement in the non-perturbative regime as well. These results are compatible with the universality of the CSS kernel in the context of jet substructure.