In gas evolving electrolysis, bubbles grow at electrodes due to a diffusive influx from oversaturation generated locally in the electrolyte by the electrode reaction. When considering electrodes of micrometre size resembling catalytic islands, direct numerical simulations show that bubbles may approach dynamic equilibrium states at which they neither grow nor shrink. These are found in undersaturated and saturated bulk electrolytes during both pinning and expanding wetting regimes of the bubbles. The equilibrium is based on the balance of local influx near the bubble foot and global outflux. To identify the parameter regions of bubble growth, dissolution and dynamic equilibrium by analytical means, we extend the solution of Zhang & Lohse (2023 J. Fluid Mech. vol. 975, R3) by taking into account modified gas fluxes across the bubble interface, which result from a non-uniform distribution of dissolved gas. The Damköhler numbers at equilibrium are found to range from small to intermediate values. Unlike pinned nanobubbles studied earlier, for micrometre-sized bubbles the Laplace pressure plays only a minor role. With respect to the stability of the dynamic equilibrium states, we extend the methodology of Lohse & Zhang (2015a Phys. Rev. E vol. 91, 031003(R)) by additionally taking into account the electrode reaction. Under contact line pinning, the equilibrium states are found to be stable for flat nanobubbles and for microbubbles in general. For unpinned bubbles, the equilibrium states are always stable. Finally, we draw conclusions on how to possibly enhance the efficiency of electrolysis.

This study aims to explore the feasibility and accuracy of utilizing large language models (LLMs) to assess the risk of bias (ROB) in cohort studies. We conducted a pilot and feasibility study in 30 cohort studies randomly selected from reference lists of published Cochrane reviews. We developed a structured prompt to guide the ChatGPT-4o, Moonshot-v1-128k, and DeepSeek-V3 to assess the ROB of each cohort twice. We used the ROB results assessed by three evidence-based medicine experts as the gold standard, and then we evaluated the accuracy of LLMs by calculating the correct assessment rate, sensitivity, specificity, and F1 scores for overall and item-specific levels. The consistency of the overall and item-specific assessment results was evaluated using Cohen’s kappa (κ) and prevalence-adjusted bias-adjusted kappa. Efficiency was estimated by the mean assessment time required. This study assessed three LLMs (ChatGPT-4o, Moonshot-v1-128k, and DeepSeek-V3) and revealed distinct performance across eight assessment items. Overall accuracy was comparable (80.8%–83.3%). Moonshot-v1-128k showed superior sensitivity in population selection (0.92 versus ChatGPT-4o’s 0.55, P < 0.001). In terms of F1 scores, Moonshot-v1-128k led in population selection (F = 0.80 versus ChatGPT-4o’s 0.67, P = 0.004). ChatGPT-4o demonstrated the highest consistency (mean κ = 96.5%), with perfect agreement (100%) in outcome confidence. ChatGPT-4o was 97.3% faster per article (32.8 seconds versus 20 minutes manually) and outperformed Moonshot-v1-128k and DeepSeek-V3 by 47–50% in processing speed. The efficient and accurate assessment of ROB in cohort studies by ChatGPT-4o, Moonshot-v1-128k, and DeepSeek-V3 highlights the potential of LLMs to enhance the systematic review process.

The evolution of settling fine particle clouds in transition or rarefied flow regimes is a fundamental yet insufficiently understood problem in fluid mechanics. Here, we address this challenge numerically using a kinematic model, and approximate the hydrodynamic interaction between particles by superposing velocity disturbances from rarefied gas flows past individual particles. The effect of electrostatic interactions among charged particles is also studied. As an application, we simulate the sedimentation of small dust clouds under Martian conditions, focusing on the 10$\,\unicode{x03BC}$m diameter fraction of ‘settled dust’. Our results show that under Martian conditions, dust clouds develop elongated tails during sedimentation, with up to 25 % of particles leaking from the bulk over a 10 minute period. Unlike Earth-based scenarios, the clouds do not break apart owing to the weaker hydrodynamic interactions in Mars’ thin atmosphere. By examining the interplay between hydrodynamic and electrostatic interactions, which influence particle leakage in opposite ways, we demonstrate that larger dust clouds are also likely to evolve with sustained tail formation. Fully suppressing particle leakage would require particle charges well above $10^4e$, levels unlikely to occur under typical Martian conditions. New analytical expressions are derived for the cloud settling velocity and tail evolution, providing theoretical insights and a foundation for future studies on particle dynamics in transition/rarefied environments.

Design-by-analogy (DbA) is a powerful method for product innovation design, leveraging multidomain design knowledge to generate new ideas. Previous studies have relied heavily on designers’ experiences to retrieve analogical knowledge from other domains, lacking a structured method to organize and understand multidomain analogical knowledge. This presents a significant challenge in recommending high-quality analogical sources, which needs to be addressed. To tackle these issues, a knowledge graph-assisted DbA approach via structured analogical knowledge retrieval is proposed. First, an improved function-effect-structure ontology model is constructed to extract functions and effects as potential analogical sources, and six semantic matching rules are established to output entity triplets, and the DbA knowledge graph (DbAKG) is developed. Second, based on the knowledge of semantic relationships in DbAKG, the domain distance and similarity between the design target and the analogical sources are introduced to establish an analogical value model, ensuring the novelty and feasibility of analogical sources. After that, with function as the design target, analogical sources transfer strategy is formed to support innovative solution solving, and TRIZ theory is used to solve design conflicts. Finally, a pipeline inspection robot case study is further employed to verify the proposed approach. Additionally, a knowledge graph-assisted analogical design system has been developed to assist in managing multidomain knowledge and the analogical process, facilitate the adoption of innovative design strategies, and assist companies in providing more competitive products to seize the market.

We present a theoretical framework for porous media gravity currents propagating over rigid curvilinear surfaces. By reducing the flow dynamics to low-dimensional models applicable on surfaces where curvature effects are negligible, we demonstrate that, for finite-volume releases, the flow behaviour in both two-dimensional and axisymmetric configurations is primarily governed by the ratio of the released viscous fluid volume to the characteristic volume of the curvilinear surface. Our theoretical predictions are validated using computational fluid dynamics simulations based on a sharp-interface model for macroscopic flow in porous media. In the context of carbon dioxide geological sequestration, our findings suggest that wavy cap rock geometries can enhance trapping capacity compared with traditional flat-surface assumptions, highlighting the importance of incorporating realistic topographic features into subsurface flow models.

The Chinese pangolin Manis pentadactyla is categorized as Critically Endangered on the IUCN Red List, but the development of effective conservation strategies is hindered by a lack of data on its distribution range and population dynamics. In addition, standardized survey and analysis methods are required to facilitate the sharing of results and maximize conservation effectiveness. To fill these knowledge and methodological gaps, we investigated the occurrence of pangolin burrows in the subtropical forest ecosystem of Fujian, China. We surveyed a total of 70 transects across five land-cover types within the Fujian Junzifeng National Nature Reserve and detected 87 burrows. The majority of burrows (87%) were located in mixed conifer and broadleaf forests. We used six environmental variables in a generalized linear model to examine the relationship between the occurrence of burrows and environmental factors. The average model results from the best model set showed that the distribution of burrows was significantly influenced by forest type. For effective pangolin conservation, we recommend that local conservation authorities prioritize the protection of mixed conifer and broadleaf forests. Our findings support the local conservation of the Chinese pangolin and the standardization of surveys and conservation efforts across the species’ range.

The late Silurian to Early Devonian floras in the South China Block provide important evidence for the radiation of early land plants, including the well-known Posongchong Formation and Xujiachong Formation of Yunnan Province and the Pingyipu Group of Sichuan Province. However, some taxa in these stratigraphic units are described on the basis of limited specimens, or even a single and/or poorly preserved specimen, and need further investigation. The re-investigation of specimen PB6458 from the Xujiachong Formation at the Xujiachong section near Xujiachong Village, Qujing City, Yunnan Province, which is the holotype of Zosterophyllum spathulatum Li and Cai, 1977, reveals some new characters of its strobilus, sporophylls, and sporangia and denies its assignment to Zosterophyllum Penhallow, 1892. Instead, this specimen should be assigned to Adoketophyton subverticillatum (Li and Cai) Li and Edwards, 1992. This taxonomic revision extends the paleogeographic distribution of Adoketophyton Li and Edwards, 1992 and further enhances this genus as one of the index fossils of Lower Devonian non-marine strata in the South China Block.

Data governance has emerged as a pivotal area of study over the past decade, yet despite its growing importance, a comprehensive analysis of the academic literature on this subject remains notably absent. This paper addresses this gap by presenting a systematic review of all academic publications on data governance from 2007 to 2024. By synthesizing insights from more than 3500 documents authored by more than 9000 researchers across various sources, this study offers a broad yet detailed perspective on the evolution of data governance research.

Femoral neck bone mineral density (FNBMD) is a high risk factor for femoral head fractures, and coffee intake affects bone mineral density, but the effect on FNBMD remains to be explored. First, we conducted an observational study in the National Health and Nutrition Examination Survey and collected data on coffee intake, FNBMD, and sixteen covariates. Weight linear regression was used to explore the association of coffee intake with FNBMD. Then, Mendelian randomisation (MR) was used to explore the causal relationship between coffee intake and FNBMD, the exposure factor was coffee intake, and the outcome factor was FNBMD. The inverse variance weighting (IVW) method was used for the analysis, while heterogeneity tests, sensitivity, and pleiotropy analysis were performed. A total of 5 915 people were included in the cross-sectional study, including 3 178 men and 2 737 women. In the completely adjusted model, no coffee was used as a reference. The ORs for the overall population at ‘< 1’, ‘1–<2’, ‘2–<4’, and ‘4+’ (95% CI) were 0.02 (–0.01, 0.04), 0.00 (–0.01, 0.02), –0.01 (–0.02, 0.00), and 0.00 (–0.01, 0.02), respectively. The male and female population showed no statistically significant differences in both univariate and multivariate linear regressions. In the MR study, the IVW results showed an OR (95% CI) of 1.06 (0.88–1.27), a P-value of 0.55, and an overall F-value of 80.31. The heterogeneity, sensitivity analyses, and pleiotropy had no statistical significance. Our study used cross-sectional studies and MR to demonstrate that there is no correlation or causal relationship between coffee intake and FNBMD.