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A bstract The pseudorapidity distribution of charged hadrons produced in Au+Au collisions at a center-of-mass energy of s NN = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover | η | < 1 . 1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

The pseudorapidity distribution of charged hadrons produced in Au+Au collisions at a center-of-mass energy of $\\sqrt{{\\textrm{s}}_{\\textrm{NN}}}$ = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover |η| < 1.1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

The pseudorapidity distribution of charged hadrons produced in Au+Au collisions at a center-of-mass energy of $\\sqrt{{\\textrm{s}}_{\\textrm{NN}}}$ = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover |η| < 1.1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

The pseudorapidity distribution of charged hadrons produced in Au+Au collisions at a center-of-mass energy of$$ \\sqrt{{\\textrm{s}}_{\\textrm{NN}}} $$s NN = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover | η | < 1 . 1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

The pseudorapidity distribution of charged hadrons produced in Au + Au collisions at a center-of-mass energy of √s̅_̅(̅N̅N̅)̅ = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover |η| < 1.1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

There is strong circumstantial evidence that certain heavy, unstable atomic nuclei are ‘octupole deformed’, that is, distorted into a pear shape. This contrasts with the more prevalent rugby-ball shape of nuclei with reflection-symmetric, quadrupole deformations. The elusive octupole deformed nuclei are of importance for nuclear structure theory, and also in searches for physics beyond the standard model; any measurable electric-dipole moment (a signature of the latter) is expected to be amplified in such nuclei. Here we determine electric octupole transition strengths (a direct measure of octupole correlations) for short-lived isotopes of radon and radium. Coulomb excitation experiments were performed using accelerated beams of heavy, radioactive ions. Our data on 220 Rn and 224 Ra show clear evidence for stronger octupole deformation in the latter. The results enable discrimination between differing theoretical approaches to octupole correlations, and help to constrain suitable candidates for experimental studies of atomic electric-dipole moments that might reveal extensions to the standard model. An experimental study of certain short-lived isotopes of radon and radium has found clear octupole deformation in the nuclei of the latter — that is, these nuclei are pear-shaped; the results enable discrimination between differing theoretical approaches to octupole correlations. Pear-shaped atomic nuclei The atomic nucleus is a many-body quantum system with a shape determined by the number of nucleons that it contains and the interactions between them. Most of the several thousand known stable and radioactive atomic nuclei, with differing numbers of protons and neutrons, are spherical or rugby-ball shaped. But there is circumstantial evidence that some heavy, unstable nuclides are distorted into a pear shape through the phenomenon of octupole deformation. Samples of these rare atomic species can be accelerated to 8% of the speed of light in the REX-ISOLDE facility at CERN, and now Coulomb excitation experiments on beams of the short-lived isotopes radium-224 and radon-220 have demonstrated clear octupole deformation in the former. The results make it possible to discriminate between the various theoretical models of octupole-deformed nuclei, and are also relevant to the pursuit of physics beyond the Standard Model.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. MRI data from more than 100 studies have been aggregated to yield new insights about brain development and ageing, and create an interactive open resource for comparison of brain structures throughout the human lifespan, including those associated with neurological and psychiatric disorders.

There is a large body of evidence that atomic nuclei can undergo octupole distortion and assume the shape of a pear. This phenomenon is important for measurements of electric-dipole moments of atoms, which would indicate CP violation and hence probe physics beyond the Standard Model of particle physics. Isotopes of both radon and radium have been identified as candidates for such measurements. Here, we observed the low-lying quantum states in 224 Rn and 226 Rn by accelerating beams of these radioactive nuclei. We show that radon isotopes undergo octupole vibrations but do not possess static pear-shapes in their ground states. We conclude that radon atoms provide less favourable conditions for the enhancement of a measurable atomic electric-dipole moment. Octupole deformation in nuclei is important to understand nuclear structure and electric dipole moments of heavy atoms. Here the authors measure energies of excited quantum states in radon isotopes and find that these isotopes do not provide favourable conditions in the search for CP-violation.

Background Determining whether MRI brain scans demonstrate atrophy that is beyond “normal for age” is challenging. Automated measurements of structural metrics in individual brain regions have shown promise as biomarkers of neurodegeneration, yet widely available reference standards that aid interpretation at the individual level are lacking. Normative modelling, enabling standardized “brain charts”, represents a significant step in addressing this challenge by generating individualized age- and sex- adjusted centile scores derived from large, aggregated datasets for MRI-derived quantitative metrics. Methods Using normative data from 56,173 participants across the life course, we have developed regional cortical thickness and amygdala/hippocampal volume brain charts (adjusted for total intracranial volume) that can be applied at the individual level. At the group level, we investigate whether regional centile scores relate to cognitive performance (mini-mental state examination) and discriminate individuals with neuropathological evidence of Alzheimer’s disease ( n  = 351) from propensity-matched controls from the National Alzheimer's Coordinating Center (NACC) dataset. In addition, we explored the relationships between disease stage, cognition, regional tau deposition and regional centile scores in amyloid-β-PET-positive individuals with Alzheimer’s disease dementia ( n  = 39) and mild cognitive impairment ( n  = 71) from the Alzheimer’s Disease Neuroimaging Initiative-3 (ADNI-3). We then extended this approach to phenotypes of frontotemporal lobar degeneration using the Neuroimaging in Frontotemporal Dementia dataset ( n  = 113). Results We demonstrate BrainChart’s application to illustrative individual cases. At the group level, we show that in Alzheimer’s disease, regional centile scores from brain charting predicted cognitive performance, temporal lobe tau PET tracer uptake and discriminated disease groups from propensity matched cognitively normal controls in independent cohorts. Distinct patterns of age-inappropriate cortical atrophy were also evident in different clinical phenotypes of frontotemporal lobar degeneration from the Neuroimaging in Frontotemporal Dementia dataset. Conclusions Regional centile scores derived from an extensive normative dataset represent a generalizable method for objectively identifying atrophy in neurodegenerative diseases and can be applied to determine neurodegenerative atrophy at the individual level.