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The place of the poorly studied mode referred to as “branching jets” in the general phenomenological classification of the modes has been determined. It has been found that the “branching jet” mode is realized only for liquids with very high dimensionless viscosities (in the region of the transition from a very viscous to a viscoelastic liquid), high electrical conductivities, and violated axial symmetry of the jet at the final stage of the phenomenon. When the “branching jet” mode is realized, the electrostatic field strength in the vicinity of the daughter jets is at the threshold of corona discharge ignition in the ambient gaseous medium. It has been shown that the “branching jet” and “fan” modes of electrodispersion differ in the electrical voltage applied to the discharge gap and in the viscosities of the liquids being dispersed.

Polyvinylidene fluoride (PVDF) is widely used in soft piezoelectric devices, where mechanical stability plays a critical role in long-term performance. In this work, the rate-dependent elastic and viscoelastic behavior of pristine PVDF films is investigated using nanoindentation. Experiments are carried out at room temperature with a maximum load of 30 mN using four different loading times (5, 10, 15, and 20 s), corresponding to loading rates of 6, 3, 2, and 1.5 mN/s, while maintaining a constant holding time of 10 s. The results show a clear loading-rate dependence, with the elastic modulus and hardness increasing by approximately 14.7 and 11.7%, respectively, as the loading rate increases. Creep compliance data obtained from the indentation hold segment are analyzed using the three-element Standard Linear Solid (Kelvin–Voigt form) and the four-element Burger model to extract the viscoelastic parameters. Comparative analysis reveals that the instantaneous elastic modulus (E₁) remains independent of loading rate in both models, whereas the delayed elastic modulus (E₂) decreases with increasing loading rate by ~31% in the SLS–K.V model and ~40% in the Burger model. Furthermore, the viscous parameters show significant rate sensitivity, with η₁ decreasing by ~57% and η₂ reducing to nearly half of its initial value at higher loading rates in both models. These results highlight the pronounced rate-dependent viscoelastic response of PVDF and provide insights relevant to the mechanical reliability of PVDF-based piezoelectric devices.

The efficiency of four modifications of flow conditioners in terms of smoothing velocity profiles and ensuring their reproducibility with varying flow history and turbulence intensity at low Reynolds numbers was experimentally studied. The relevance of the work is due to the problem of increasing the accuracy of gas flow measurement in complex gas-dynamic conditions, especially in the region of laminar–turbulent transition. An approach has been identified that allows for the leveling of velocity profile deformations in a wide range of flow histories with a flow turbulence level not exceeding 14% and down to a lower Reynolds number value of 943.

This study aims to investigate the nontransitivity of the stochastic precedence relation. The dice were taken as an example of discrete random variables with a finite set of values. The means and variances of the dice were assumed those of the classical dice. The whole variety of nontransitive sets containing three or four dice were found in case of one or two tosses and various ways to determine the advantage. The sets that reveal the strongest property of nontransitivity were obtained according to the specific function. The hypothesis has been tested about the emergence of nontransitivity after two tosses of dice in originally transitive sets.

The rapid growth of electronic waste has intensified the need for sustainable approaches for metal recovery from waste printed circuit boards (WPCBs). In this study, betaine-based natural deep eutectic solvents (NADES) were developed as lixiviants for metal extraction from WPCBs. Betaine (BET) was used as the hydrogen bond acceptor, while ethane-1,2-diol (ETD), propane-1,2-diol (PPD), and butane-1,2-diol (BTD) served as hydrogen bond donors (HBDs) to investigate the influence of HBD structure on the physicochemical properties and leaching performance of the resulting NADES. Fourier transform infrared spectroscopy (FTIR) indicated intermolecular interactions between BET and the diol-based HBDs, while thermogravimetric analysis/derivative thermogravimetry (TGA/DTG) showed pronounced mass-loss-rate maxima above 240 °C for all three NADES. Rheological measurements revealed Newtonian flow behaviour, with viscosity increasing with increasing diol chain length; BET:ETD exhibited the lowest viscosity (50.1 mPa·s) at 20 °C. Under the experimental conditions of 75 °C, 6 h, 1.0 M H₂O₂, 500 rpm, and a solid-to-liquid ratio of 1:20, BET:ETD achieved leaching efficiencies of 99.3% for Cu, 99.5% for Pb, 97.8% for Fe, 95.4% for Al, 90.5% for Sn, and 73.9% for Ti. Kinetic analysis based on the shrinking core model and activation energy evaluation indicated a mixed-control mechanism involving interfacial reaction and diffusion processes. SEM, XRD, and FTIR analyses further indicated substantial dissolution of metallic phases while the polymeric and glass-fibre matrix was largely preserved. Overall, the results demonstrate that betaine-based NADES, most especially BET:ETD, offer tunable physicochemical properties and effective metal-leaching performance for WPCB recycling.

To investigate the spatiotemporal variability of lead (Pb) in mining environments, 100 topsoil samples were collected from different locations across a semi-arid mining district in western Iran over a 4-month monitoring period, with sampling conducted at different sites in each month. Key explanatory variables, namely, pH, electrical conductivity (EC), soil organic carbon (SOC), zirconium (Zr), and elevation and slope as topographic attributes alongside normalized difference vegetation index (NDVI), were integrated into the Geographic and Temporal Weighted Regression (GTWR) framework. Pb was selected because of its strong association with mining activities, high environmental persistence, and ecological significance. The effectiveness of the GTWR model was evaluated and compared with Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR) and Temporally Weighted Regression (TWR) using multiple statistical evaluation metrics and model-fitting criteria. In addition, the ecological implications of Pb contamination were assessed using the risk quotient (RQ) index. The evaluation metrics demonstrated the superiority of GTWR (R² = 0.79) over the other models. The results indicate that Pb distribution was influenced by geological, geochemical, and biological factors, with Zr showing a predominantly spatially positive association, EC exhibiting spatially variable effects, and NDVI and pH showing relatively stable temporal associations with Pb. Furthermore, RQ values exceeded the ecological threshold throughout the study area, indicating widespread potential ecological risk. Integrating GTWR with ecological risk assessment provides a useful framework for characterizing heterogeneous Pb patterns and supporting the identification of priority areas for environmental monitoring and risk management in mining-affected landscapes.

Ground-level ozone (O₃) has become a major challenge for air quality improvement in China, but its short-term variability is controlled by complex interactions among pollutant persistence, precursor conditions, and meteorological factors. In this study, hourly air quality observations and ERA5 reanalysis meteorological data for an urban monitoring site in Wuhan during 2019-2025 were integrated to evaluate O₃ temporal variability and interpretable machine learning prediction. Three models, namely, deep neural network (DNN), random forest (RF), and extreme gradient boosting (XGBoost), were compared using baseline and lag-enhanced feature sets, and SHapley Additive exPlanations (SHAP) were used to interpret predictive contributions. O₃ remained at relatively high levels during 2019-2025, with exceedances of the national grade II standard in 2019, 2023, and 2024, while most primary pollutants generally declined. O₃ exhibited a unimodal diurnal cycle with afternoon peaks at 14:00-16:00 and a seasonal pattern of summer > spring > autumn > winter. The enhanced XGBoost model achieved the best short-term prediction performance, with R² = 0.9756 and RMSE = 6.35 μg m^-3 on the test set. SHAP analysis showed that the 1-h lagged O₃ concentration was the dominant predictor, indicating strong short-term persistence rather than independent chemical forcing. NO₂ and lagged NO₂ showed negative predictive contributions, consistent with the expected role of NO titration under high-NOₓ conditions, whereas temperature and radiation-related variables showed positive contributions. These results suggest that interpretable machine learning can help identify the statistical conditions associated with O₃ variability, but the absence of direct VOC observations means that O₃ sensitivity and VOC-related control implications should be further verified using VOC measurements or chemical transport/observation-based modeling.