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Work participation disparities among LGBTQ+ Australians: Insights from a nationally representative cohort study
This study examined work participation disparities among lesbian, gay, bisexual, transgender, queer, and other sexually and/or gender diverse (LGBTQ+) adults using nationally representative data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. Sexual identity data were collected in wave 20 (2020) from 14,302 participants and gender identity data in wave 23 (2023) from 13,981 participants. Multivariable regression models examined associations between sexual or gender identity and work participation measures. Sexual identity was analysed cross-sectionally (wave 20) and longitudinally (waves 20–23), while gender identity was analysed cross-sectionally (wave 23). Compared to heterosexual participants, those identifying as gay or lesbian were more likely to be unemployed (prevalence ratio [PR] 2.05, 95% CI 1.01–4.14) and less likely to work in trades or manual occupations (PR 0.55, 95% CI 0.36–0.85) or in manufacturing and construction (PR 0.40, 95% CI 0.23–0.72). Bisexual participants had higher prevalence of labour force non-participation (PR 1.91, 95% CI 1.49–2.47) and unemployment (PR 2.05, 95% CI 1.24–3.38), and were less likely to work in agriculture, forestry or mining (PR 0.24, 95% CI 0.08–0.79). Participants of other sexual identities also had higher unemployment (PR 2.78, 95% CI 1.41–5.45). Longitudinally, bisexual participants were more likely to transition out of employment (incidence rate ratio [IRR] 2.08, 95% CI 1.35–3.21) and initiate paid sick leave (IRR 1.42, 95% CI 1.17–1.71), while gay or lesbian participants were more likely to commence working from home (IRR 1.72, 95% CI 1.21–2.44). Transgender and gender diverse participants were less likely to work in manufacturing and construction (PR 0.35, 95% CI 0.17–0.75) and worked fewer hours (PR 0.88, 95% CI 0.79–0.97) than cisgender peers. These findings highlight inequalities in work participation among LGBTQ+ adults, underscoring the need for dedicated research and inclusive workplace policies.
Decoding atomic landscapes: Integrating electronic structure theory and high-resolution atomic force microscopy
High-resolution atomic force microscopy (HR-AFM) has emerged as a transformative technique for imaging and manipulating matter with atomic precision. By functionalizing the scanning probe with a CO molecule, HR-AFM enables direct visualization of chemical bonds, intermolecular interactions, charged states, and electron orbital signatures. We provide an overview of HR-AFM from both experimental and theoretical perspectives. The operational principles of frequency-modulation AFM and the role of tip functionalization are described, together with methods that combine AFM and STM for enhanced imaging and spectroscopy. Theoretical approaches, such as the virtual tip method, full density functional theory, frozen density embedding theory, and tip-tilting correction methods, enable the quantitative interpretation of tip–sample interactions and image contrast. These developments support applications of HR-AFM in resolving bond orders, functional groups, heteroatoms, and orbital fingerprints in single molecules, as well as in characterizing complex industrial hydrocarbons. Beyond imaging, HR-AFM also serves as a platform for controlled bond rupture and manipulation at the atomic scale. The benchmark Si(111)-(7 × 7) surface is revisited with recent insights into tip-induced contrast dynamics arising from B doping. Extensions of HR-AFM to state-resolved imaging of quantum defects in two-dimensional materials are also discussed. By combining high-resolution imaging with first-principles modeling, HR-AFM demonstrates a unique capability to reveal previously inaccessible surface phenomena, thereby further decoding the atomic landscapes of matter at the single-atom and molecular scale.
Nitric Oxide Reduction at a Single Iron Site Facilitated by Second Coordination Sphere Hydrogen Bonding via a Putative Fe(IV)-Oxo Intermediate
Public interest in biodiversity and climate change: A comparative culturomics study of China and the UK
Understanding how the public engages with biodiversity loss and climate change is critical for designing effective environmental policies and conservation strategies. Here we applied a conservation culturomics approach to compare public interest in biodiversity and climate change across China and the United Kingdom, two major environmental actors with distinct governance models and cultural contexts. Using search volume data from the Baidu Index and Google Trends between 2011 and 2022, we identified peak periods of search interest in both countries. We then analysed associated news content during peak and non-peak periods using grounded theory and thematic coding to uncover the dominant drivers of public attention. Our findings reveal a stark contrast between sources of public engagement. In China, the public interest is predominantly state-driven, with peaks aligned with government-led campaigns and international events. Themes, such as domestic governance and ecological civilisation, were the most significant. In the UK, civil society, scientific discourse, and environmental activism act as the key catalysts in shaping public engagement. These differences reflect greater variations in political structures, media ecosystems, and cultural values. Our results highlight the need for context-sensitive communication strategies. By linking digital behaviour with media discourse we offer new insights into public environmental engagement. Our findings further suggest that enhancing bottom-up participation and diversifying environmental narratives in China could foster greater public ownership of conservation efforts, whereas in the UK maintaining inclusive and coherent narratives is essential. However, limitations such as platform algorithms should be considered when interpreting these cross-country comparisons, as they may affect the comparability of search data between Baidu Index and Google Trends.
Statistical mechanical theory and computational study on thermodynamic stability of clathrate hydrates
Clathrate hydrates are non-stoichiometric inclusion compounds with critical relevance to energy resources and CO2 sequestration, formed by guest molecules encapsulated in water cages. This perspective overviews the synergistic progress achieved through statistical mechanics and molecular simulation with intermolecular potential models in three key areas: thermodynamic stability, structural polymorphism, and dynamic processes. Theoretical estimation of its stability, originated from the van der Waals and Platteeuw theory, has been greatly improved by revisions accounting for constant pressure conditions, multiple occupancy, and host–guest coupling, enabling accurate prediction of multi-phase coexistence. Novel hydrate and ice structures have been synthesized using new strategies. The Frank–Kasper HS-I phase is unstable with small gas molecules, however, it was realized as a semiclathrate hydrate with an alkyl ammonium salt. We also discuss several possible strategies to form metastable ices, such as degassing of gas hydrates. The dynamic aspects have been investigated using molecular dynamics simulations. It was shown that dissociation kinetics are significantly influenced by guest concentration and bubble formation. Molecular dynamics simulations have also provided valuable insights into two types of low dosage hydrate inhibitors.
What happened and what proves you wrong? Combatting confirmation bias in police investigations through evidence reconstruction and falsification
Confirmation bias in criminal investigations has repeatedly been linked to wrongful convictions. Drawing on principles from the Scenario Reconstruction Method, developed for and used in Dutch policing, this study tested whether shifting the investigative focus from identifying suspects to reconstructing scenarios based on available evidence could reduce confirmation bias. In addition, the design included a theoretically motivated manipulation encouraging falsification over verification. The result was a 2 (focus: suspect vs. evidence) × 2 (strategy: verification vs. falsification) factorial online study involving 293 current and future German police officers, who analysed a real wrongful conviction case from the Netherlands. The primary outcome was the accuracy of guilt ratings for the innocent suspect; secondary outcomes assessed the type of proposed next investigative steps. The analyses showed the manipulations had no effect on guilt ratings. However, both strategies did influence investigative reasoning: evidence-focus increased the likelihood of proposing more evidence-based next investigative steps, while falsification-focus promoted more falsification-oriented next investigative steps. Cross-over effects suggested a broader shift in investigative mindset toward more objective reasoning. Future research should explore whether these early improvements in reasoning translate into more accurate outcomes when progressing from brief instructions to multi-stage interventions such as the full Scenario Reconstruction Method.
Supercritical water at ten densities from 0.1 to 1.0 gr/cc at 1000 K using <i>ab initio</i> molecular dynamics simulations
Supercritical water is found inside Earth’s mantle, where water is subjected to very high temperatures and pressures. It exhibits extraordinary properties, such as having a low dielectric constant and high reactivity, which stems from the breakdown of the hydrogen bond network in a supercritical state. This makes supercritical water a non-polar solvent and the basis for many innovative technologies. We investigate supercritical water at ten densities (0.1–1.0 gr/cc) at 1000 K to study the structural correlations, such as atom-resolved partial pair distributions, co-ordination numbers, bond-angle distributions and neutron scattering, and x-ray structure factors. Among the dynamical correlations, we investigate the velocity autocorrelation function, current–current correlation function, and their Fourier transforms—vibrational density-of-states and frequency dependent dielectric constant. Structural and dynamical correlations are computed from time-trajectories of the positions and velocities calculated ab initio molecular dynamics within the density functional theory framework using the SCAN exchange–correlation functional. Our results for structural correlations are compared with the neutron scattering experiments on supercritical water by Soper and collaborators [J. Chem. Phys. 106, 247–254 (1997)] and dynamical correlations in the supercritical state are compared with the inelastic neutron scattering results by Car and collaborators [J. Phys. Chem. Lett. 11, 9461–9467 (2020)].
Associations between sleep duration and depression, mental health, physical health, and general health in U.S. adults: A population-based study
Introduction Adequate sleep is vital for maintaining mental and physical health. In the United States, a substantial proportion of adults report sleep durations that fall outside the recommended range. Prior research has associated insufficient or excessive sleep with adverse health outcomes; however, few studies have systematically quantified these associations across multiple health indicators using nationally representative data. Objective This study aims to evaluate the impact of short sleep duration on four key health outcomes: depression diagnosis, number of self-reported poor mental health days, number of physically unhealthy days, and self-rated general health status, using nationally representative U.S. data. Methodology: Methods We analyzed nationally representative data from the Behavioral Risk Factor Surveillance System (BRFSS) collected between 2016 and 2023. Sleep duration was self-reported and categorized into three groups: short sleep (≤5 hours), recommended sleep (6–8 hours), and long sleep (≥9 hours), with short sleep serving as the reference category. The primary health outcomes included: (1) self-reported diagnosis of depression, (2) number of poor mental health days, (3) number of poor physical health days, and (4) self-rated general health, measured on a 5-point Likert scale from excellent to poor. To estimate the effect of sleep duration on these outcomes, we applied Inverse Probability Weighting (IPW) to derive the Average Treatment Effect (ATE), adjusting for key demographic and socioeconomic covariates. All analyses incorporated BRFSS complex survey weights to ensure national representativeness. Results The study included 318,000 adults (63.3% female; 74.5% White) with a mean age of 51.3 ± 18.4 years. Among individuals with recommended sleep duration (6–8 hours), the baseline prevalence of depression was 39.5% (95% CI: 39.4%–39.7%). Compared to this group, short sleep duration (≤5 hours) was associated with a 14.1 percentage point increase in depression incidence (95% CI: 13.8%–14.4%), while long sleep duration (≥9 hours) was linked to a 12.9 percentage point increase (95% CI: 12.5%–13.3%). Those with short sleep reported an average of 5.3 poor mental health days (95% CI: 5.3–5.4), 4.4 poor physical health days (95% CI: 4.3–4.4), and a higher prevalence of poor general health, 10.0% (0.1, 95% CI: 9.7%–10.2%), compared to individuals with recommended sleep. Similarly, individuals with long sleep duration (≥9 hours) also reported more poor mental (4.6 days, 95% CI: 4.5–4.7) and physical health days (3.2 days, 95% CI: 3.1–3.3), along with a higher prevalence of poor general health, 20.3% (20.3%%, 95% CI 19.4%–21.3%) compared to those with recommended sleep. Conclusion Both short (≤5 hours) and long (≥9 hours) sleep durations are significantly associated with increased risk of depression, more days of poor mental and physical health, and worse self-rated general health compared to recommended sleep (6–8 hours). Promoting optimal sleep duration through targeted public health interventions, education, and screening may improve population well-being and reduce sleep-related health disparities.
Restricted open-shell time-dependent density functional theory with perturbative spin–orbit coupling: Inclusion of spin-flip-down states
Calculating electronically excited states for molecular systems with an electronic configuration that has two or more unpaired electrons remains a challenge in quantum chemistry. The electronically excited states are often hard to model due to the complex nature of the wave function. This especially holds true in the case of heavy-element systems, for which the treatment of spin–orbit coupling (SOC) is crucial for a good description. To address this, we have modified the SOC-corrected restricted open-shell Kohn–Sham (ROKS) time-dependent density functional theory approach within the Tamm–Dancoff approximation (TDA). We have extended the ROKS-TDA-SOC method by including scalar relativistic spin-flip-down states (in addition to the spin-conserved and spin-flip-up ones) from ROKS-TDA, which participate in the SOC state interaction. Our assessment shows that ROKS-TDA-SOC is able to efficiently calculate the lowest-lying SOC-split excitation energies in molecular systems that contain heavy elements and two or more unpaired electrons.
No pets allowed: Evidence that prolonged grief disorder can occur following the death of a pet
Background Prolonged grief disorder (PGD) is a psychiatric disorder in ICD-11 and DSM-5-TR that can only be diagnosed following the death of a person. Despite considerable evidence that people form strong attachments to their pets, and experience high levels of grief following their death, the current guidelines do not allow PGD to be diagnosed following the death of a pet. This study tested several hypotheses to determine if there is anything unique about grief that follows the death of a person versus grief that follows the death of a pet. Methods A nationally representative sample of adults from the United Kingdom ( N = 975) provided information about different bereavements, their most distressing bereavement, and ICD-11 PGD symptoms. Results One-third (32.6%) of respondents experienced the death of a beloved pet, and almost all had also experienced the death of a human; 21.0% of these people chose the death of their pet as most distressing. The conditional rate of PGD following the death of a pet was 7.5%, similar to many types of human losses. The relative risk of PGD following pet bereavement was 1.27, and pet loss accounted for 8.1% of all PGD cases in the population, both of which were higher than many types of human losses. Full measurement invariance for PGD symptoms was found between people who reported symptoms for a human bereavement and for a pet bereavement. Conclusions People can experience clinically significant levels of PGD following the death of a pet, and PGD symptoms manifest in the same way regardless of the species of the deceased. Implications associated with excluding diagnosis following pet bereavement are discussed.
Erratum: “Unique proton transfer and hydrogen evolution reaction at semi-disordered interfaces in confined spaces” [J. Chem. Phys. 163, 144708 (2025)]
Ultracold D + H2 ( <i>v</i> = 4, <i>j</i> = 0) reaction dynamics: Long-range interactions, diagonal Born–Oppenheimer correction, and a diabatic geometric phase treatment
Ultracold hydrogen-exchange reactions have long provided a key platform for identifying subtle quantum mechanical effects in triatomic systems. The long-range interactions, diagonal Born–Oppenheimer correction (DBOC), and geometric phase (GP) have been predicted to influence such reactions, yet their individual effects have not been investigated. Here, we investigate the D + H2(v = 4, j = 0) → H + HD reaction using time-dependent wave packet calculations that incorporate a newly constructed long-range potential, DBOC, and a diabatic GP treatment. The inclusion of the accurate long-range interactions substantially alters the cold reaction dynamics by removing spurious short-range barriers and strongly modifying partial-wave resonances, including a pronounced shift and nearly 70% enhancement of the J = 2 resonance. The DBOC produces a modest overall reduction in the reaction rate, whereas the GP introduces the dominant suppression and governs the interference pattern in both total and state-resolved rates. These results demonstrate that the accurate inclusion of long-range interactions, DBOC, and GP is essential for reliably describing ultracold hydrogen–deuterium exchange reactions, clarifying the distinct roles each contribution plays in the reaction dynamics.
Divergent Total Synthesis of the Harziane Diterpenoids
Air-Stable Tetrazene Radical Cation Salts: Structural Requirements and Oxidation Catalysts
An explicit solvent model of coacervate structure and thermodynamics
Complex coacervation, a liquid–liquid phase separation phenomenon driven by electrostatic interactions between oppositely charged polyelectrolytes (PEs), has attracted widespread attention because of its relevance in biological systems and potential applications in materials science. Although many theoretical models, experimental investigations, and computational studies have investigated the thermodynamics, phase coexistence behavior, and rheological properties in great detail, a molecular-level understanding of the internal structure of the complex coacervate phase is still lacking. In this study, we investigate the effects of the degree of polymerization of the polyelectrolytes (N) on the phase behavior and internal structure of the resulting coacervate phase using molecular dynamics simulations employing a simplistic bead–spring model of polyelectrolytes and explicit nonpolar solvents. Our simulations show an increase in coacervate phase stability with N, elevating the critical temperature in agreement with existing theoretical predictions and experimental observations. The polyelectrolytes inside the dense phase maintain a homogeneous overlapping distribution without collapsing into globules. The compactness of the dense phase increases with N in agreement with prior experimental observations, despite a concomitant increase in the polymer’s effective size as quantified by its radius of gyration (Rg). We discuss the implications of this model for a fundamental understanding of the coacervation process and as a first step toward the systematic examination of the mutual role of electrostatics and chemistry in the behavior of solvated polyions.
Computation-Guided Placement of Nonfullerene Acceptor Core Halogenation for High-Performance Organic Solar Cells
Phase separation morphology of immiscible polystyrene/poly(methyl methacrylate) single-chain nanoparticle blend films
Regulating the phase morphology structure is crucial for the fabrication of multifunctional and high performance polymer blend films. In this work, we investigate the phase separation morphology evolution of immiscible polystyrene/poly(methyl methacrylate) single-chain nanoparticle (PS/PMMA SCNP) blend films prepared by spin coating. The results show that the composition of the morphological transition from sea-island structure to co-continuous structure is between 40/60 and 35/65 in PS/PMMA linear precursor blend films, while it is between 35/65 and 30/70 in PS/PMMA SCNP blend films. The phase-separated domains of the SCNP blend films are much smaller than those of linear precursor blend films. Moreover, the domain height of PMMA SCNP-containing blends is lower than that of PS/PMMA linear precursor blends, indicating the decreased solubility of PMMA SCNPs in chloroform. X-ray photoelectron spectroscopy results reveal that the mass fraction of the PMMA component on the surface of PMMA linear precursor blend films is higher than that of PMMA SCNP blend films with the same composition, leading to different phase separation morphologies of these two blend films. The rheological results prove that the viscosity of the PS/PMMA SCNP blend solution is higher than that of the PS/PMMA linear precursor blend solution; thus, the diffusion and local relaxation of PMMA SCNPs are slower during spin-coating. Consequently, the phase separation is suppressed and the domain size decreases in PS/PMMA SCNP blend films. The phase separation process induced by the replacement of linear polymer chains by SCNPs could have significant implications for industrial applications requiring soft nanocomposite materials with excellent nanoparticle dispersion.
Highly Acidic Second Coordination Spheres Promote In Situ Formation of Iron Phlorins Exhibiting Fast and Selective CO <sub>2</sub> Reduction
Non-Gaussian self-diffusion in binary mixtures of highly charged colloids
We quantify non-Gaussian diffusion in binary mixtures of dilute, highly charged colloids in three dimensions and compare mean-square displacements ⟨[Δrx(t)]2⟩ and fourth moments ⟨[Δrx(t)]4⟩ obtained from Brownian dynamics with the prediction of multi-component mode-coupling theory (MCT). Using structure factors of systems with a reduced number of effective charges as input, with a rescaled MCT scheme, a quantitative agreement of theoretical predictions for the long-time self-diffusion coefficients DS,x(L) and simulation results is obtained. Rescaled MCT predicts larger non-Gaussian parameters α2,x(t) than those obtained from simulations, which are shifted to shorter times than found in simulations. We observed for the second non-Gaussian parameter α2,x(t) dynamical coupling effects in mixtures of identically charged particles with different short-time diffusion coefficients D0,x.