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  • Continuous-time sampler performs well for trans-dimensional Bayesian inference

    What the study found

    The paper presents samsara, a continuous-time Markov chain Monte Carlo framework for Bayesian analysis when the number of parameters is unknown. The authors report that it achieved automatic acceptance of trans-dimensional moves and high sampling efficiency in the cases they tested.

    Why the authors say this matters

    The authors state that Bayesian inference becomes difficult when the parameter space is large and unknown, including in mixture models with an unknown number of components and overlapping-signal problems such as the laser interferometer space antenna global fit problem. They conclude that samsara is a powerful alternative to reversible-jump Markov chain Monte Carlo for large and variable-dimensional Bayesian inference problems.

    What the researchers tested

    The researchers developed a continuous-time Markov chain Monte Carlo, or CTMCMC, framework that uses Poisson-driven birth, death, and mutation processes to model parameter evolution. They required detailed balance through adaptive rate definitions and included waiting-time weighted estimators, optimized memory storage, and a modular design. They validated the code on three benchmark problems: an analytic trans-dimensional distribution, joint inference of sine waves and Lorentzians in time series, and a Gaussian mixture model with an unknown number of components.

    What worked and what didn't

    In all three benchmark cases, the code showed excellent agreement with analytical results and nested sampling results. The abstract says this included an analytic trans-dimensional distribution, time-series inference with sine waves and Lorentzians, and a Gaussian mixture model with unknown component count. The abstract does not report any failing cases or quantitative performance limits.

    What to keep in mind

    The summary provided here is limited to the abstract, so only the reported benchmark tests and general claims are available. The abstract does not describe numerical benchmarks, detailed comparisons, or limitations of the method.

    • samsara is a continuous-time Markov chain Monte Carlo framework for Bayesian problems with unknown dimension
    • the authors say it automatically accepts trans-dimensional moves through adaptive rate definitions
    • the code was tested on three benchmark problems, including a Gaussian mixture model with unknown components
    • the abstract reports excellent agreement with analytical results and nested sampling results
    • the authors conclude it is a powerful alternative to reversible-jump Markov chain Monte Carlo

  • Empirical expectations strongly shaped double-surname intentions in Italy

    What the study found

    The study found that people’s empirical expectations, meaning what they think others actually do, had a stronger influence on intentions to give children a double surname than normative expectations, meaning what they think others approve of. The authors report that this pattern appeared in Italy after a 2022 Constitutional Court ruling allowed children to take a double surname unless parents agreed otherwise.

    Why the authors say this matters

    The authors conclude that changing empirical expectations may be important for encouraging the adoption of double surnames. They suggest this could support greater gender equality in family naming practices.

    What the researchers tested

    The researchers used two survey experiments with Italian online quota samples. Respondents were randomly assigned to one of four hypothetical scenarios designed to change their empirical and normative expectations about double surnames.

    What worked and what didn't

    In the first experiment, empirical expectations had a stronger effect on intentions than normative expectations. The second experiment confirmed this pattern, but the effect depended on which reference network was considered.

    What to keep in mind

    The abstract does not provide details about sample size, effect sizes, or the exact content of the hypothetical scenarios. It also does not describe limitations beyond noting that the second experiment’s effect depended on the reference network considered.

    • The study focused on intentions to adopt double surnames for children in Italy.
    • Empirical expectations were more influential than normative expectations.
    • Two survey experiments were conducted with Italian online quota samples.
    • The second experiment found that the effect depended on the reference network considered.
    • The authors link the findings to greater gender equality in family naming practices.

  • Starobinsky model remains compatible in parts of parameter space

    What the study found

    The study found that a significant region of parameter space for the Starobinsky inflation model is still consistent with the latest observational data. It also reports that adding a cubic R^3 curvature correction can move the model's predictions closer to the Planck and Atacama Cosmology Telescope (ACT) measurements.

    Why the authors say this matters

    The authors note that the latest ACT sixth data release, combined with DESI DR2 baryon acoustic oscillation (BAO) data, appears to exclude the pure Starobinsky model at about the 2-sigma level. The study suggests that the model may still remain a compelling candidate for cosmic inflation, and that curvature corrections may help align it with observations.

    What the researchers tested

    The researchers analyzed the Starobinsky inflation model and the effect of curvature corrections, especially a cubic R^3 term. They implemented the Starobinsky inflationary potential directly into the CLASS code without using the slow-roll approximation, and they constrained the number of e-folds of inflation, N_k, using a theoretically motivated range based on reheating considerations and standard couplings between matter fields and gravity.

    What worked and what didn't

    The pure Starobinsky model appears to be in tension with the latest ACT plus DESI DR2 results, according to the abstract. However, the study reports that there is still a substantial region where the model fits the data well, and that including a cubic R^3 term can improve agreement with Planck and ACT measurements.

    What to keep in mind

    The abstract does not provide detailed numerical limits beyond the reported 2-sigma tension and the measured scalar spectral index. It also does not describe all model assumptions or give a full account of uncertainties beyond the stated observational comparison.

    • The abstract reports that a significant region of Starobinsky inflation parameter space remains consistent with recent data.
    • ACT DR6 combined with DESI DR2 BAO data appears to exclude the pure Starobinsky model at roughly the 2-sigma level.
    • The researchers used the CLASS code and did not rely on the slow-roll approximation.
    • A cubic R^3 curvature correction is reported to shift predictions closer to Planck and ACT measurements.
    • The number of e-folds, N_k, was constrained using reheating considerations and standard matter-gravity couplings.

  • Iron and myelin susceptibility changes linked to stroke outcome

    What the study found

    The study found that deep gray matter nuclei in people with acute ischemic stroke showed susceptibility alterations that could be separated into iron-related and myelin-related components. In this sample, measures from the dentate nucleus and thalamus were associated with 3-month functional outcome.

    Why the authors say this matters

    The authors conclude that separating paramagnetic susceptibility, which reflects iron-related effects, from diamagnetic susceptibility, which reflects myelin-related effects, may reveal pathophysiological changes that conventional quantitative susceptibility mapping can miss. The study suggests these measures may help relate deep gray matter changes to functional independence after stroke.

    What the researchers tested

    The researchers prospectively studied 82 people with acute ischemic stroke and 82 healthy controls using 3 T MRI with a 3D multi-echo gradient-echo sequence. They applied χ-separation to measure paramagnetic and diamagnetic susceptibility in several deep gray matter nuclei, then tested group differences and associations with 3-month functional independence.

    What worked and what didn't

    Compared with healthy controls, patients had higher paramagnetic susceptibility in all seven nuclei studied, including the dentate nucleus and thalamus. They also had higher diamagnetic susceptibility in the caudate, putamen, red nucleus, thalamus, and dentate nucleus; poor 3-month outcome was independently associated with higher dentate nucleus paramagnetic susceptibility, higher dentate nucleus diamagnetic susceptibility, and higher thalamus paramagnetic susceptibility.

    What to keep in mind

    The abstract does not describe major limitations in detail. The analysis was restricted to contralesional nuclei in patients, and the outcome measure was functional independence at 3 months, defined by modified Rankin Scale scores of 0–2 versus 3–6.

    • χ-separation was used to separate iron-related and myelin-related susceptibility signals in deep gray matter nuclei.
    • People with acute ischemic stroke showed higher paramagnetic susceptibility in all seven nuclei studied.
    • Higher diamagnetic susceptibility was found in the caudate, putamen, red nucleus, thalamus, and dentate nucleus.
    • Poor 3-month outcome was independently associated with dentate nucleus and thalamus susceptibility measures.
    • A combined model with χ-separation metrics performed better than a conventional model alone.

  • MOPBnB(so) approximates Pareto optimal sets in stochastic optimization

    What the study found

    The study presents Multiple Objective Probabilistic Branch and Bound with Single Observation (MOPBnB(so)), an algorithm for approximating the Pareto optimal set and the associated efficient frontier in stochastic multi-objective optimization. The authors report finite-time performance results for deterministic problems and asymptotic convergence results for stochastic problems.

    Why the authors say this matters

    The authors suggest the method is relevant because it can approximate the Pareto optimal set while using fewer computational resources than a variant that relies on multiple replications. They also conclude that the approach outperforms the genetic algorithm NSGA-II on the test problems they studied.

    What the researchers tested

    The researchers tested MOPBnB(so), which evaluates a noisy function exactly once at any solution and uses neighboring solutions to estimate objective functions. They compared it with a variant that uses multiple replications at a solution, and they also evaluated it against NSGA-II on numerical test problems.

    What worked and what didn't

    The abstract states that a finite-time analysis for deterministic multi-objective problems gives a bound on the probability that MOPBnB(so) captures the Pareto optimal set. It also states that, for stochastic problems, the algorithm captures the Pareto optimal set and its estimates converge to the true objective values. The multiple-replication variant is described as extremely intensive in computational resources, and MOPBnB(so) is reported to outperform NSGA-II on the test problems.

    What to keep in mind

    The abstract does not provide details on the specific test problems, the size of the benchmarks, or the conditions under which the comparison was made. It also does not describe limitations beyond the note that the multiple-replication variant is computationally intensive.

    • MOPBnB(so) is designed to approximate Pareto optimal sets and efficient frontiers in stochastic multi-objective optimization.
    • The algorithm uses a single noisy evaluation at each solution and estimates objectives from neighboring solutions.
    • The abstract reports finite-time performance bounds for deterministic problems and asymptotic convergence for stochastic problems.
    • A multiple-replication version is described as extremely computationally intensive.
    • Numerical results show MOPBnB(so) outperforms NSGA-II on the test problems.
  • Wave-like reactivity may explain Windscale criticality incident

    Wave-like reactivity may explain Windscale criticality incident

    What the study found

    The study found that a wave-like reactivity variation may have governed the Windscale Works criticality incident. The authors report that the short-duration inrush and the stable emulsion might both have influenced the criticality, with the effective multiplication factor exceeding 1 under some conditions.

    Why the authors say this matters

    The authors conclude that their findings support a hypothesis about the incident's criticality mechanism. They suggest this helps clarify a previously unclear criticality scenario by linking the event to time-varying reactivity, meaning changes in how readily a nuclear chain reaction can sustain itself.

    What the researchers tested

    The researchers performed a multiphysics analysis, combining computational fluid dynamics (CFD, computer simulations of fluid flow) with Monte Carlo neutron transport calculations. They examined the effects of a short-duration inrush and a stable emulsion, then used simplified wave-like reactivity variations in neutronic kinetics analyses.

    What worked and what didn't

    According to the abstract, the CFD results produced space- and time-dependent material distributions that were used to evaluate the effective multiplication factor. The results suggest that both the inrush and the stable emulsion might have contributed to conditions where the effective multiplication factor exceeded 1, and the simplified kinetics analyses were consistent with historical records under certain conditions.

    What to keep in mind

    The abstract describes a possible mechanism rather than a confirmed reconstruction of the incident. It also notes that the detailed criticality scenario remains unclear, and the compatibility with historical records is stated only for certain conditions.

    • The study proposes that a wave-like reactivity variation may have governed the Windscale Works criticality incident.
    • The analysis considered a short-duration inrush and a stable emulsion, which were not included in the previous study.
    • CFD results were used to create space- and time-dependent material distributions for neutron transport calculations.
    • The results suggest the effective multiplication factor may have exceeded 1 under some conditions.
    • Simplified neutronic kinetics analyses were consistent with historical records under certain conditions.
  • Tick bite and DSCATT are linked to distinct circulating miRNA changes

    Tick bite and DSCATT are linked to distinct circulating miRNA changes

    What the study found

    The study found that tick bite and Debilitating Symptom Complexes Attributed to Ticks (DSCATT) were associated with changes in circulating host microRNAs, which are small molecules that help regulate gene expression. The authors also identified a five-microRNA signature that classified acute tick bite with 86% accuracy.

    Why the authors say this matters

    The authors conclude that these findings highlight potential biomarkers and possible mechanisms underlying chronic symptom development. The study suggests this may help explain host responses to tick bite and DSCATT.

    What the researchers tested

    The researchers profiled circulating host-encoded microRNAs in two cohorts: a longitudinal cohort followed after tick bite for up to 12 months, and a retrospective cohort with DSCATT. They used differential expression analysis, temporal clustering, predicted target pathway analysis, and machine learning.

    What worked and what didn't

    In the longitudinal cohort, tick bite was associated with 149 microRNAs that varied significantly over 12 months. In the DSCATT cohort, 98 microRNAs were differentially expressed, with overlap between DSCATT and acute tick bite microRNAs; four microRNAs also correlated with symptom severity, including fatigue and dizziness. The five-microRNA classifier identified acute tick bite with 86% accuracy and a receiver operating characteristic area under the curve of 0.92.

    What to keep in mind

    The abstract does not describe study limitations in detail. It also states that the biological mechanisms remain unclear, so the findings are about associations and candidate biomarkers rather than established causes.

    • Tick bite was associated with widespread changes in circulating host microRNAs over 12 months.
    • DSCATT patients showed 98 differentially expressed microRNAs.
    • Four microRNAs correlated with symptom severity, including fatigue and dizziness.
    • A five-microRNA signature classified acute tick bite with 86% accuracy and ROC AUC of 0.92.
    • Predicted target pathways were enriched for immune modulation, tissue remodelling, and cellular stress responses.

  • Time-delay combinations differ in detecting axion-like dark matter

    What the study found

    The study found that different time-delay interferometry combinations in space-based gravitational wave detectors have different sensitivity ranges for detecting axion-like dark matter. Monitor and Beacon are better at high frequencies, while Sagnac is better at low frequencies.

    Why the authors say this matters

    The authors conclude that adding additional wave plates may enable detectors to respond to axion-induced birefringence, which is the change in polarization caused by the axion-like dark matter. They also indicate that ASTROD-GW may be able to cover axion-like dark matter masses down to 10^-20 eV.

    What the researchers tested

    The researchers calculated and compared the sensitivities of different space-based gravitational wave detectors. They considered three time-delay interferometry combinations: Monitor, Beacon, and Relay.

    What worked and what didn't

    Monitor and Beacon had better sensitivity in the high-frequency range, and the optimal sensitivity reached about g_aγ ~ 10^-13 GeV^-1. The Sagnac combination performed better in the low-frequency range. The abstract says current designs are insensitive to variations in polarization angle unless additional wave plates are used.

    What to keep in mind

    The summary provided here is limited to the abstract, so details of the calculations, detector assumptions, and uncertainties are not described. The abstract does not give full performance comparisons for every detector beyond the main frequency-range findings.

    • Different time-delay interferometry combinations have different sensitivity ranges for axion-like dark matter.
    • Monitor and Beacon are more sensitive at high frequencies.
    • Sagnac is more sensitive at low frequencies.
    • The best sensitivity reported is about g_aγ ~ 10^-13 GeV^-1.
    • ASTROD-GW may reach axion-like dark matter masses down to 10^-20 eV.

  • Soviet judge elections combined citizen oversight with party influence

    What the study found

    The article finds that the election and recall of People’s Court judges in Soviet Russia were presented as a form of people’s control, with citizens formally involved in choosing and removing judges. It also finds that Communist Party and administrative bodies influenced both the pre-election stage and the final outcomes.

    Why the authors say this matters

    The authors conclude that these procedures showed distinctive features of Soviet social control and helped shape judicial recruitment. The study suggests that identifying which parts worked and which did not may offer historical insights for modern judicial recruitment reforms.

    What the researchers tested

    The author examined the institutional frameworks and procedures for electing and recalling People’s Court judges in Soviet Russia. The study used regulatory legal acts from the Soviet era to describe these mechanisms and their role in judicial composition.

    What worked and what didn't

    According to the abstract, the procedures did engage citizens in overseeing judicial composition. At the same time, the article says Communist Party and administrative influence affected the process, and it critically evaluates the actual performance of these mechanisms in managing judicial recruitment.

    What to keep in mind

    The abstract does not provide detailed findings about specific election or recall cases. It also does not give a full account of all limitations, beyond noting that the study evaluates the mechanisms’ actual performance within the Soviet legal framework.

    • People’s Court judges in Soviet Russia could be elected and recalled by citizens.
    • The article describes legal rules and procedures for those election and recall mechanisms.
    • Citizen involvement coexisted with Communist Party and administrative influence.
    • The study evaluates how well these procedures managed judicial recruitment.
    • The authors suggest the findings may offer historical insight for modern reform discussions.

  • Jet lobe growth follows self-similar scaling in simulations

    What the study found

    The study found that active galactic nucleus (AGN) jets, which are outflows from galactic centers, can show jet lobe growth that follows analytic self-similar scaling relations in the simulated self-similar regime. It also found that the energy split between thermal and kinetic energy departs from the idealized picture.

    Why the authors say this matters

    The authors say these results establish robust benchmarks for smoothed particle hydrodynamics (SPH, a particle-based fluid simulation method) jet modelling. They also state that the findings provide insight into the physical and numerical factors shaping jet–medium interactions and lay the groundwork for future AGN feedback studies in more realistic galactic and cluster environments.

    What the researchers tested

    The researchers used the smoothed particle hydrodynamics code gadget4-Osaka to simulate AGN jet evolution in the self-similar regime. They systematically varied jet-launching schemes, artificial-viscosity prescriptions, mass resolution, and jet lifetimes, and compared the results with grid-based simulations.

    What worked and what didn't

    Jet lobe growth converged with resolution and followed analytic self-similar scaling relations. The overall jet size tracked self-similar predictions, but the partitioning of thermal and kinetic energy differed significantly from the idealized picture, with enhanced dissipation and mixing; this behavior was described as consistent with jet propagation in grid-based simulations. The results were highly sensitive to the choice of artificial viscosity.

    What to keep in mind

    The abstract focuses on the self-similar regime, so the summary does not describe behavior outside that regime. It also does not give detailed limitations beyond noting sensitivity to artificial-viscosity choices and the dependence on simulation setup.

    • AGN jet lobe growth followed analytic self-similar scaling relations in the simulations.
    • The growth converged with increasing resolution.
    • Results were highly sensitive to the artificial-viscosity prescription.
    • Thermal and kinetic energy partitioning departed from the idealized picture.
    • Enhanced dissipation and mixing were observed and were consistent with grid-based simulations.