Entanglement is a key property of quantum systems. In this Letter the first measurements of quantum entanglement between spins in pairs of Z bosons are reported, using proton-proton collision data from the Large Hadron Collider (LHC) at center-of-mass energies of 13 and 13.6 TeV, recorded with the ATLAS detector. Measurements of angular observables sensitive to ZZ^{*} spin-density-matrix elements in the H→ZZ^{*}→ℓ^{+}ℓ^{-}ℓ^{+}ℓ^{-} process yield coefficients C_{2,1,2,-1}=-0.71±0.45 and C_{2,2,2,-2}=0.08±0.44, consistent with their Standard Model predictions. A complementary hypothesis test using the full angular distribution, and relying on several Standard Model assumptions in the decays, provides substantially higher sensitivity to quantum correlations and disfavors the separable-state hypothesis at a significance of 4.7 standard deviations (expected 4.9σ) relative to the entangled Standard Model hypothesis. These results provide strong evidence of quantum entanglement between massive bosons (spin qutrits) at the electroweak scale.

This Letter presents the first evidence of the simultaneous production of two Z bosons and one photon with the ATLAS detector at the Large Hadron Collider. The measurement is performed using the full Run-2 dataset, recorded from 2015 to 2018, of proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 140 fb^{-1}. The fully leptonic final state with four leptons and one photon is analyzed, pp→ZZγ→ℓ^{+}ℓ^{-}ℓ^{'+}ℓ^{'-}γ with ℓ,ℓ^{'}=e or μ. This final state is measured in a fiducial region where photon final-state radiation is minimized, and the photon has a transverse momentum of p_{T}^{γ}>20 GeV. Eight events are selected, with a background estimate of 0.92±0.15. This results in an observed (expected) significance of the ZZγ final state of 4.4σ (4.0σ). The measured cross section for pp→ZZγ→ℓ^{+}ℓ^{-}ℓ^{'+}ℓ^{'-}γ in the fiducial region is σ_{ZZγ}=0.144_{-0.051}^{+0.065}(stat)_{-0.004}^{+0.008}(syst) fb, in agreement with the standard model prediction of σ_{fid}^{SM}=0.130±0.006 fb.

This Letter reports on the first evidence of inclusive Higgs-boson production at high transverse momentum in the bb[over ¯] final state, reconstructed in a single large-radius jet. The results are based on proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider at a center-of-mass energies of 13 and 13.6 TeV, corresponding to a total integrated luminosity of 301 fb^{-1}. The study profits from the large background suppression provided by the use of a new transformer-based algorithm for jet identification and the sharper mass and transverse momentum, p_{T}, resolution from a dedicated regression model. The yield relative to the standard model prediction for Higgs bosons produced at p_{T} larger than 450 GeV is measured to be 1.53±0.27)_{-0.27}^{+0.33}±0.17, where the first uncertainty is statistical, the second is experimental systematic, and the third accounts for theory systematic, corresponding to an observed (expected) significance of 3.8σ(2.5σ) relative to the background-only hypothesis. Results are also obtained in three Higgs boson p_{T} intervals and found to be compatible with standard model predictions, where the first uncertainty is statistical, the second is experimental systematic, and the third accounts for theory systematic.

A combination of measurements of the CP properties of Higgs boson interactions with electroweak gauge bosons is presented, using 140 fb^{-1} of proton-proton collisions at sqrt[s]=13 TeV recorded by the ATLAS detector. Results from vector boson fusion H→ττ/WW^{*}/γγ, inclusive H→ZZ^{*}, and WH,H→bb[over ¯] channels are combined. No evidence of CP violation is observed, and constrains on the CP-violating operators in the Standard Model effective field theory framework (SMEFT) are set in the Warsaw basis. The results from the combination improve by over 40% on previous individual limits on c_{HW[over ˜]} and, for the first time, simultaneous constraints on three coefficients c_{HW[over ˜]}, c_{HB[over ˜]}, and c_{HW[over ˜]B} are set. These limits are the most stringent constraints to date on the relevant Wilson coefficients in the SMEFT framework with minimum model dependence.

Type 1 diabetes begins with autoimmunity against pancreatic islet antigens, including insulin. The aim of the Primary Oral Insulin Trial (POInT) was to evaluate the efficacy and safety of daily high-dose oral insulin to prevent the development of islet autoantibodies and diabetes.

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures.

Objective: Missed patient appointments have a substantial negative impact on patient care, child health and well-being, and clinic functioning. This study aims to identify health system interface and child/family demographic characteristics as potential predictors of appointment attendance in a pediatric outpatient neuropsychology clinic. Method: Pediatric patients (N = 6,976 across 13,362 scheduled appointments) who attended versus missed scheduled appointments at a large, urban assessment clinic were compared on a broad array of factors extracted from the medical record, and the cumulative impact of significant risk factors was examined. Results: In the final multivariate logistic regression model, health system interface factors that significantly predicted more missed appointments included a higher percentage of previous missed appointments within the broader medical center, missing pre-visit intake paperwork, assessment/testing appointment type, and visit timing relative to the COVID-19 pandemic (i.e. more missed appointments prior to the pandemic). Demographic characteristics that significantly predicted more missed appointments in the final model included Medicaid (medical assistance) insurance and greater neighborhood disadvantage per the Area Deprivation Index (ADI). Waitlist length, referral source, season, format (telehealth vs. in-person), need for interpreter, language, and age were not predictive of appointment attendance. Taken together, 7.75% of patients with zero risk factors missed their appointment, while 22.30% of patients with five risk factors missed their appointment. Conclusions: Pediatric neuropsychology clinics have a unique array of factors that impact successful attendance, and identification of these factors can help inform policies, clinic procedures, and strategies to decrease barriers, and thus increase appointment attendance, in similar settings.

T-tests from 42 brain tumor patients showed adaptive functioning below normative means at both time points (test interval M=2.60y, SD=1.32). Neurological risk, time since diagnosis,age at diagnosis, age at evaluation, and time since evaluation were correlated with specific adaptive skills. There was a main effect of age at diagnosis, age at assessment, time since diagnosis, and neurological risk as well as an interaction of age at diagnosis × neurological risk for specific adaptive skills. Results highlight the importance of considering the relationship between developmental and medical variables on changes in adaptive functioning in survivors of pediatric brain tumors.