Given two subsets X,Y of a finite group G, we write Pr(X,Y) for the probability that random elements x∈X and y∈Y commute. If X,Y are subgroups, we denote by Pr⁎(X,Y) the maximum real number ϵ with the property that for every pair of distinct primes p∈π(X) and q∈π(Y) there is a Sylow p-subgroup P of X and a Sylow q-subgroup Q of Y such that Pr(P,Q)≥ϵ.In this paper we handle, among other things, finite groups G with high probabilities Pr⁎(T,G), where T is either a term of the lower central series of G or the generalized Fitting subgroup Fi⁎(G). Our main results show that the structure of such groups is similar, in some precise sense, to that of nilpotent groups.
Research on cognitive abilities, including cognitive profiles, language, and executive functioning, of autistic females is still scarce and results are contrasting. We conducted a PRISMA systematic review, including 22 studies (agreement = 94,59
Leveraging complementary machine-learning-based approaches, we compute properties of s- and p-shell A hypernuclei-including binding energies, single-particle densities, and radii-starting from the individual interactions among their constituents. These interactions are modeled based on a leading-order finite-cutoff pionless effective field theory expansion. The couplings and the range of the three-nucleon and A-nucleon-nucleon potentials are determined via a Gaussian process framework anchored on virtually exact few-body techniques. We solve the many-body Schr & ouml;dinger equation using a variational Monte Carlo method based on neural network quantum states, extending it for the first time to include A particles alongside protons and neutrons. The predicted binding energies show remarkably good agreement with experimental results, given the simplicity of the input Hamiltonian. We also confirm the experimentally observed shrinkage of the proton radius in 7 Li compared to its parent nucleus, 6Li. This work paves the way for an ab initio description of medium-mass and heavy hypernuclei, which is critical for understanding the onset of strange degrees of freedom in the core of neutron stars.
Hypnotizability is a psychophysiological trait associated with structural variation in brain regions implicated in time perception, such as the cerebellum and the insula. This study investigated time reproduction across different interval durations in individuals with varying levels of hypnotizability. Forty healthy, right-handed participants of both sexes were assessed using the Stanford Hypnotic Susceptibility Scale: Form A and completed a time reproduction task consisting of visually presented intervals of 1, 3, 6, and 8 s (10 trials per duration). Relative proportional error (RE) and absolute proportional error (AE) were analyzed using mixed-effects models estimating the interaction between hypnotizability and interval duration through polynomial contrasts, with random intercepts and duration slopes for participants. Heart rate, sex, trait anxiety, and absorption were included as covariates. RE showed only a significant main effect of interval duration, with shorter intervals overestimated and longer intervals underestimated. AE showed a significant interaction between hypnotizability and the linear component of interval duration, indicating that higher hypnotizability was associated with a steeper decrease in AE as interval duration increased. The relatively lower precision at shorter intervals is consistent with attenuated sensory processing, whereas the relatively higher precision at longer intervals may reflect better functional coupling between executive and salience networks previously observed in highly hypnotizable individuals. The reduced precision at shorter intervals may be more consistent with cerebellar than insular involvement. Differences in time perception may be linked to reported associations between hypnotizability and an altered sense of agency and body ownership.
The global shift toward sustainability has amplified interest in the Circular Economy, which aims to optimize resource use and minimize waste. In parallel, the Sustainable Development Goals (SDGs) provide a universal framework for addressing social, environmental, and economic challenges. This study bridges academic research and corporate practice by mapping how Circular Economy strategies and SDG priorities are articulated across domains. By identifying who leads on what and where convergence occurs, it seeks to guide cross-fertilization, foster mutual learning, and support more aligned sustainability transitions. While prior research highlights the transformative potential of circularity frameworks, few studies examine how these ideas are unevenly adopted across institutional settings. To address this, we conduct a comparative textual analysis of 919 academic articles and the sustainability reports of the top 50 Fortune 500 firms for the period 2015-2024, using computational linguistic methods to trace links between circular strategies and SDGs targets. The findings reveal a more nuanced landscape than a simple academia-industry divide. Although their fourth priorities differ, "Repurpose" for academia and "Repair" for firms, both domains emphasize upstream circular strategies such as "Refuse", "Rethink", and especially "Reduce". Convergence also emerges around SDG 7 (clean energy), SDG 12 (responsible consumption), and SDG 13 (climate action). The study reframes the academia-industry gap as a dynamic relationship and proposes a map of Circular Economy SDG alignments to guide future collaboration.
