Search Results (359)

This work investigates the effect of specific electrolytes (NaCl, KCl, MgCl₂, and CaCl₂) on bubble coalescence and the stability of the resulting foam caps in aqueous sodium dodecyl sulfate (SDS) solutions. At low concentrations, we observe that all electrolytes studied exhibited a similar effect on bubble coalescence, driven primarily by the electrostatic screening of the repulsion between bubbles. However, a distinct divergence in behavior emerges at higher concentrations: KCl and CaCl₂ destabilize the foam, while NaCl and MgCl₂ act as foam boosters. By applying Pitzer’s theory and the concept of cohesive pressure, we propose that foam stability is governed by the hydration compatibility between the surfactant head groups and the salt ions. We describe a mechanism in which the “cohesive pressure” of the water matrix determines the efficiency of the SDS adsorption layer. Specifically, strong kosmotropic ions (e.g., Mg²⁺) preserve the hydration shell of the sulfate head groups, thereby preventing film collapse, whereas ions with lower dehydration energy (e.g., Ca²⁺) are proposed to facilitate the formation of contact ion pairs, thereby promoting rapid coalescence. Full article

To address the issues of low water and fertilizer use efficiency and limited yield potential in traditional winter wheat cultivation in Henan Province, and to determine the optimal drip irrigation frequency for wide-row precision sowing under a constant total irrigation amount, this study was conducted based on a field experiment in Zhengzhou, Henan, during the 2024–2025 season. Four treatments were set up: border irrigation with wide-row precision sowing (QK40), and single-drip irrigation events of 25 mm (DK25, high frequency), 40 mm (DK40, medium frequency), and 55 mm (DK55, low frequency). The effects of drip irrigation frequency on photosynthetic accumulation after anthesis (AUC), source–sink coordination index (SSCI), and the synergy among water, grain, and quality in wide-row precision-sown winter wheat were quantitatively analyzed. The results showed that DK25 significantly delayed leaf senescence and extended the green leaf functional period by 9 days by stabilizing moisture in the 0–40 cm root zone. Post-anthesis photosynthetic accumulation increased by 23.39% and was highly significantly positively correlated with yield. The leaf area index at the heading stage increased by 23.54%, and the source–sink coordination index (SSCI) improved by 45.1%. Over the whole growth period, water consumption was reduced by 10.38%, water use efficiency increased by 23.5%, and yield increased by 8.9%, while grain quality remained stable. Entropy Weight-TOPSIS evaluation showed that DK25 performed the best. This study can provide a cultivation pattern and technical parameters for water-saving, high-yield, and high-quality wide-row precision-sown winter wheat in the Huang-Huai-Hai Plain. Full article

Drought stress significantly constrains broccoli (Brassica oleracea L.) productivity by impairing growth, photosynthesis, and yield. Seed priming with ascorbic acid (AsA) has shown promise in enhancing early seedling performance; however, its effects on head development and yield under water deficit remain limited. This greenhouse pot experiment evaluated four seed treatments: non-primed control, water-primed control, 1 mg L⁻¹ AsA, and 10 mg L⁻¹ AsA under two irrigation regimes: 100% and 50% field capacity. Growth, physiological traits, biochemical responses, and yield were assessed. AsA priming significantly (p < 0.05) enhanced plant height, net photosynthesis, and chlorophyll content under both water regimes. Under 100% FC, water priming significantly increased canopy length, whereas under 50% FC, only AsA priming produced a significant increase relative to the non-primed control (p < 0.05). Biochemical responses further showed that 10 mg L⁻¹ AsA significantly (p < 0.05) increased chlorophyll a and chlorophyll b under 50% FC compared with the non-primed control. Proline accumulation was reduced by 10 mg L⁻¹ AsA, but this reduction was significant (p < 0.05) only under 100% FC. Under 100% FC, 10 mg L⁻¹ AsA significantly (p < 0.05) increased total phenolic content compared with the non-primed control. Total flavonoid content was significantly (p < 0.05) increased by 1 and 10 mg L⁻¹ AsA compared with the control, while both water priming and AsA priming significantly (p < 0.05) increased carotenoid content and reduced H₂O₂ accumulation relative to the non-primed control, irrespective of watering regime. Total yield per plant, measured on a fresh weight basis, significantly (p < 0.05) increased with increasing AsA concentration, with 10 mg L⁻¹ AsA enhancing yield by 37.8% relative to the water-primed control and by 70.5% relative to the non-primed control, independent of water regime. Percentage dry weight was unaffected by AsA treatment. Overall, AsA seed priming potentially enhanced physiological resilience and fresh yield of broccoli under water-limited conditions, indicating its potential as a low-cost strategy for drought mitigation. Full article

A modular and automated cleaning device for floating solid waste was developed to tackle the problems of low collection efficiency, high energy consumption, and frequent clogging in rural ditches and ponds. According to field monitoring data, the inlet velocity and filter mesh size were determined. The device comprises a cleaning module, a collection module, and a bottom filter connected in series, which is driven mainly by gravity with low-power electric control as assistance. CFD and FEA were employed to simulate the flow field around the cleaning roller, the stress of the retention plate, and the head loss of the bottom filter. The results demonstrate that the flow field on the cleaning roller is stable, and the maximum velocity exhibits a linear relationship with the inlet velocity. The maximum equivalent stress of the retention plate is 38.6 MPa, and the rubber head can absorb more than 80% of the impact energy. With a 3 mm aperture for the bottom filter, the head loss is about 26 mm at the designed flow rate, achieving a good balance between interception efficiency and low flow resistance. The device can effectively intercept floating waste such as plastics and straws, making it suitable for routine cleaning of small rural water bodies. Full article

The middle reaches of the Minjiang River, shaped by the Dujiangyan irrigation system, provide a typical setting for studying long-term human–water interactions. During the Little Ice Age, the water management system as a whole experienced a full cycle of recovery, expansion, and decline from 1644 to 1949 (Qing to Republican period), although subregions exhibited marked spatial heterogeneity. This heterogeneity makes the area an ideal case for comparative analysis; however, previous studies have neither quantitatively reconstructed river–canal changes nor systematically disentangled the composite natural and anthropogenic drivers across different subregions. Using archival documents, historical maps, remote sensing imagery, and water cultural heritage sites, this study reconstructs the evolution and quantifies two change types: anthropogenic construction, including new construction, reconstruction, and modification, and environmentally driven changes such as rerouting, damage, and maintenance. Correlations were analyzed among the four subregions: Inner River, Outer River, Nanhe River, and the Lower Basin to identify driving mechanisms. Results indicate that anthropogenic construction is constrained by natural conditions and driven by population growth, whereas environmentally driven changes are primarily caused by floods and worsened by canal head maintenance failure. The four spatially differentiated driving patterns are: Inner River—human-dominated intervention type; Outer River—flood stress type; Nanhe River—low-disturbance stable type; and Lower Basin—natural–human composite type. This study offers new insights into long-term human–water interactions in large irrigation districts under climate change. Full article

Rice–fish co-culture is widely promoted for mitigating nitrous oxide (N₂O) emissions from paddy soils, yet how the duration of co-culture reshapes the underlying nitrogen-cycling microbial community under low-nitrogen input remains poorly understood. This study aimed to (i) characterize how co-culture duration alters the rhizosphere microbial functional potential for N₂O production and consumption, and (ii) identify the water and soil variables linking fish activity to that response. The experiment was conducted during the 2024 rice growing season in the Qingtian rice–fish system (Zhejiang Province, China), a traditional agricultural heritage system managed without chemical fertilizer or supplementary feed. Three treatments (i.e., rice monoculture, first-year co-culture, and long-established (~10-year) co-culture) were compared using six independently bunded replicate plots each. Rhizosphere soils were collected at the tillering, heading and maturity stages for shotgun metagenomic profiling of nitrogen-cycling functional genes, with concurrent measurement of N₂O flux and water and soil physicochemical properties. Fluxes were uniformly low and did not differ among treatments (p > 0.05), defining a substrate-limited baseline. Against this baseline, first-year co-culture induced a coordinated shift toward complete denitrification (nosZ increased by 25–33% across all stages; nosZ/(nirK + nirS) rose to 0.99 at heading), associated with a transient water organic carbon pulse and dissolved-oxygen availability. The long-established system resembled monoculture, indicating a non-monotonic, duration-dependent response. Full article

With the large-scale development of renewable energy such as wind, solar and ocean energy, the demand for energy storage is more urgent. Pumped hydro energy storage (PHES) is one of the fundamental solutions to the problem of intermittent supply of renewable energy. The large-capacity/low-head pumped hydro energy storage (LL-PHES) system with the use of tubular pump turbine is a beneficial extension of traditional PHES systems owing to large flow rate and cheaper civil structures. However, the continuous competition between the “static water pressure difference caused by gravity” and the “pressure increase caused by accelerated impeller rotation” leads to prominent instability in the start-up process of the LL-PHES system under pump conditions. An explicit coupling algorithm is proposed for analyzing the transient characteristics in the start-up process of the LL-PHES system under pump conditions. This algorithm is based on the idea of dimensional transformation, and performs 3D flow calculations and 2D rigid body dynamics equation solution in the pump domain and the flap gate domain, respectively. This algorithm avoids the problems of high computational cost and poor convergence that exist in existing fully three-dimensional coupling algorithms and ensures the efficiency of transient hydraulic characteristic calculation. A comprehensive analysis of the transient characteristics of the LL-PHES system during pump start-up process is conducted using the proposed new algorithm. The entire process of the increase in rotational speed, valve opening, flow rate, and the continuous evolution of blade surface pressure during the start-up process is quantitatively described. The amplitude and spectral characteristics of the alternating pressure on multiple blades are clarified. The evolution law of blade load during the stage of severe pressure fluctuations during the start-up process is explained. The load distribution characteristics of “high in the leading and trailing edge areas and low in the middle” in the blade stream direction is presented. The research results have a direct guiding role in improving the hydraulic design and enhancing the operational stability of LL-PHES systems. Full article

Multivariate time-series anomaly detection on physical sensor networks faces three challenges that generic deep learning models inadequately addressed: heterogeneous sensor reliability, context-dependent anomaly scoring, and inactionable binary outputs lacking per sensor attribution. We propose an uncertainty-aware Temporal Convolutional Network (TCN) framework built on two tightly integrated uncertainty-driven components: (i) an Adaptive Uncertainty-Aware Attention (AUAA) mechanism that gates temporal attention weights by per sensor predictive uncertainty obtained from Monte Carlo dropout; and (ii) a Dynamic Weight Adapter that learns context-sensitive blending of reconstruction error and uncertainty via a GRU over weight history. The architecture also includes an exploratory per sensor attribution head, which we audit rather than claim: a controlled-perturbation test shows it is not yet causally faithful. We complement the empirical architecture with two distribution-free theoretical results: a Chebyshev-type false-positive bound on the hybrid anomaly score, and a Monte Carlo posterior moment convergence result at rate $O\left(M^{-1/2}\right)$. Evaluated on four-month indoor air quality sensor data, the Full Enhanced model achieves $R^2=0.9988$ and MSE $1.65\times {10}^{-4}$, a $25.2\%$ MSE reduction over the Base TCN ($R^2=0.9984$, MSE $2.20\times {10}^{-4}$). Because the IAQ stream is unlabeled, the primary quantitative detection evaluation uses the labeled Skoltech Anomaly Benchmark (SKAB), a publicly available industrial water-circulation corpus disjoint from the IAQ training distribution; it yields an 8.8 × F1 advantage ($0.477$ vs. $0.054$) and a 14.4 × recall advantage ($0.418$ vs. $0.029$) for the proposed model configuration over the Base TCN at a validation-calibrated threshold applied without retuning. Against twelve established detectors under a unified protocol, the proposed model attains the best F1 and recall, while the strongest reconstruction baselines retain higher precision and a marginally higher ROC-AUC, a recall-driven trade-off. Ablation isolates each component’s contribution, the detector degrades gracefully under channel masking and noise, and the distribution-free false-positive bound is empirically respected. The framework retains a low inference cost ($0.16$ ms per window at $M=20$ Monte Carlo samples, including the uncertainty pass). Full article

Improving the irrigation water effective utilization coefficient (IWEUC, η) is important for improving agricultural water management and reducing pressure on agricultural water resources. However, in humid agricultural regions, the main factors associated with observed IWEUC improvement remain uncertain. They could be either interannual climate variability or structural improvements in irrigation engineering and management. Using measurement data from 202 representative irrigation districts in Hunan Province, China, from 2014 to 2022, this study combined the head–tail measurement method, comparative trend analysis, and correlation analysis to distinguish climate-related variability from structural change. Province-wide η increased from 0.4884 to 0.5502, and differences among large, medium-sized, and small districts narrowed over time. Structural differences also remained evident. Pumped systems generally showed higher efficiency and faster improvement than gravity-fed systems, and medium-sized gravity-fed districts remained the main low-efficiency category. No stable significant relationships were found between η and hydrometeorological indicators, whereas water-saving investment showed a positive association with η, with the strongest positive association observed in medium-sized gravity-fed districts. These results suggest that IWEUC improvement in humid agricultural regions is more closely associated with structural modernization related to engineering investment and management improvement than with annual hydrometeorological variability. Full article

To clarify the effects of pond excavation and field elevation combined with biochar application on soil improvement and maize growth in cold-soaked fields in northern China, a two-year field experiment was conducted using maize as the test crop under five biochar application rates: 0, 7.5, 15, 22.5, and 30 t/ha. The effects of biochar application on soil water characteristics, maize root development, plant growth, and yield formation were investigated. The results showed that, under the pond excavation and field elevation treatment, the application of 22.5 t/ha biochar (B3) achieved the best overall improvement effect and significantly improved soil moisture conditions. At the heading stage, the soil water content in the 0–90 cm soil layer under the B3 treatment increased by 6.18% and 27.72% in the two experimental years, respectively, compared with the 0 t/ha biochar treatment (B0). In 2025, compared with the B0 treatment, root length density, root surface area density, and root volume density under the B3 treatment increased by 38.56%, 109.31%, and 65.35%, respectively, while the average diameter of maize fine roots decreased by 8.50%. Meanwhile, the leaf area index, plant height, stem diameter, kernels per ear, 100-kernel weight, and maize yield were all significantly increased, with grain yield reaching 13,991.10 kg/ha in 2025. Correlation analysis showed that the biochar application rate was significantly positively correlated with maize plant height, stem diameter, leaf area index, root morphological traits, and grain yield, indicating that biochar application promoted maize growth and yield by optimizing canopy structure and root architecture. These results demonstrate that pond excavation and field elevation combined with an appropriate biochar application rate can effectively improve cold-soaked fields in northern China and achieve stable and high maize yields, thereby providing technical support for the management of medium- and low-yield farmlands. Full article

Pump-as-turbine (PAT) units have been widely used for energy recovery in water-supply networks, petrochemical systems, and small hydropower applications; however, their turbine-mode performance is often limited because most commercial pumps are originally designed for pumping conditions. To improve the hydraulic performance of a low-specific-speed PAT, this study developed a surrogate-assisted multi-objective optimization framework combining three-dimensional computational fluid dynamics (CFD), design of experiments, a Kriging surrogate model, and a multi-objective genetic algorithm. Five key impeller geometric parameters, including blade inlet angles, blade wrap angles, and impeller outlet diameter, were selected as design variables, and turbine-mode efficiency was maximized under a head constraint of H ≥ 24 m at the rated condition of 1450 r/min. The results showed that the optimized design increased efficiency from 72.34% to 84.42% while satisfying the head requirement. Comparative analyses of pressure and velocity fields in the impeller and volute further revealed that the performance improvement was mainly associated with enhanced flow-field uniformity and reduced local hydraulic losses. A dedicated PAT test rig was finally established to experimentally validate the optimized design. Full article

Two-dimensional transition metal carbides and nitrides, known collectively as MXenes, are attractive photocatalyst candidates because their surface chemistry and atomic composition can be tuned over a wide compositional window. A crucial design quantity is the electronic bandgap, which selects whether a given MXene couples with solar radiation and aligns with the redox levels of water splitting. High-fidelity bandgap calculations using the PBE0 hybrid functional are computationally expensive, which has motivated several machine learning surrogates. To the best of our knowledge, this is the first study to integrate a continuous-depth Neural Ordinary Differential Equation backbone with multi-fidelity $\Delta$ learning, distribution-free split-conformal calibration, and uncertainty-aware Pareto screening into a single mathematically grounded pipeline for MXene bandgap prediction. In this work, we develop a physics-constrained neural ordinary differential equation (PC-NODE) that predicts MXene bandgaps from a compact 34-dimensional descriptor set, without relying on the density of states. The model couples a classifier head for the metal/semiconductor decision with a regression head for the gap magnitude, and enforces three physically motivated properties: non-negativity of the predicted gap and monotonicity between the low-fidelity Perdew–Burke–Ernzerhof (PBE) and the high-fidelity PBE0 estimates are obtained exactly through a softplus-parameterised $\Delta$ learning construction, while a hurdle coupling that drives metal predictions towards zero is enforced via a quadratic penalty and verified empirically. In short, two of the three physical constraints are guaranteed by construction, and the third is approximately enforced and verified empirically; the same distinction is maintained consistently in the methodology, the constraint audit and the conclusion. Trained on the 4356-structure MXgap database, a ten-seed ensemble reaches a mean absolute error of $0.186$ eV (per-seed $0.206\pm 0.006$ eV) and a coefficient of determination $R^2=0.880$ on the semiconductor test subset, with a classifier accuracy of $0.856$ and a Receiver Operating Characteristic Area Under the Curve (ROC-AUC) of $0.925$. A split-conformal calibration step then delivers prediction intervals whose empirical coverage matches the 90% target within 0.5 percentage points. Finally, an uncertainty-aware Pareto screening step applies the trained surrogate to a held-out subset of 396 lanthanum-based MXenes and identifies 74 candidates inside the photocatalytic water splitting window [1.23, 3.10] eV. The framework offers a mathematically grounded, data-efficient alternative to feature-heavy pipelines and is reproducible from the open MXgap resource. Full article

To deliver freshwater for drip irrigation, our study presents an optimal techno-economic based on a Water Pumping Photovoltaic System (WPPVS) that integrates a Hydrogen Energy Storage System (HySS) to ensure reliable freshwater for agricultural irrigation in remote arid regions. A critical operational challenge in WPPVS is mechanical vibration at low flow rates, which degrades the pump efficiency and lifespan. Our methodology directly addresses this issue by incorporating a vibration-avoidance strategy that ensures that the pump operates only within its stable and, efficient range. To reduce the loss of water supply probability and overall annual costs of the drip irrigation system, a multi-objective optimization framework using Multi-Objective Particle Swarm Optimization (MOPSO) and Gaussian Mixture Model (GMM) clustering to simultaneously minimize the Loss of Water Supply Probability (LWSP), and the system’s total life-cycle cost. The model’s practical applicability is demonstrated through a detailed techno-economic feasibility analysis for a tomato crop drip irrigation project in Sakaka, Saudi Arabia. Sensitivity analysis is performed on dynamic head, crop prices, and interest and inflation rates, confirming the robustness of the system against variable economic indicators. In comparison to 1071 h without HySS, the results revealed that the seasonal irradiation harvest hours are 1863, which represents 21% of the seasonal hours employing the developed hybrid energy storage coordination. This integrated approach provides a holistic and economically viable solution for designing reliable solar irrigation systems with long-term mechanical integrity. Full article

This paper presents a temperature field analysis and a new water-cooling channel design for a 1000 kW, 72-slot/8-pole permanent magnet synchronous motor used in mining applications. To capture temperature rise data related to electromagnetic losses and fluid heat transfer, a multiphysics coupling model was established, and its accuracy was verified through temperature rise experiments on a prototype. To address the issues of poor temperature uniformity and excessive head loss in the original structure, a double-helix return cooling water channel structure was designed, effectively compensating for the heat exchange capacity at the motor ends and reducing fluid resistance. Comparative analysis shows that this structure significantly outperforms traditional cooling water channels in terms of heat dissipation efficiency, temperature uniformity, and pressure loss. Under optimal geometric parameters—10 spiral turns and a flow velocity of 1 m/s—the maximum winding temperature was suppressed to 67.7 °C, with a winding temperature difference of only 2.6 °C, while the pressure drop was maintained at a low level of 9580 Pa. This study provides a theoretical basis and an efficient engineering solution for the design of water-cooling structures in large mining motors. Full article

Background and Objectives: Knee osteoarthritis (KOA) is a degenerative joint disease that affects quality of life through pain, impaired functional performance, and altered gait patterns. Hydrotherapy is a well-tolerated form of physical rehabilitation, especially suitable for patients with severe pain, as water’s properties support movement while reducing joint load. Its effects have been widely studied, primarily focusing on patient-reported outcomes, with limited synthesis of functional performance and gait-related outcomes. Materials and Methods: A systematic search was conducted in PubMed, Web of Science, Cochrane, PEDro, SpringerLink, ScienceDirect, and Google Scholar, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search strategy included a combination of Medical Subject Headings (MeSH) terms and keywords. For example, the PubMed search strategy was as follows: (“knee osteoarthritis” OR “knee OA”) AND (“hydrotherapy” OR “aquatic therapy” OR “water-based exercise”) AND (“gait” OR “walking” OR “functional performance”). Randomized controlled trials (RCTs) from the last 10 years involving patients with KOA undergoing aquatic therapy were included. Primary outcomes included functional performance assessed by measures such as the 6 min walking test (6MWT), the Timed Up and Go (TUG) test, the five sit-to-stand (5 STS) and stair climb (SC) tests, and by using gait-related parameters (e.g., speed, cadence, and step length) assessed clinically or using technology. Patient-reported outcomes, including the Visual Analog Scale (VAS), Western Ontario and McMaster University’s Osteoarthritis Index (WOMAC), and Knee Injury and Osteoarthritis Outcome Score (KOOS), were analyzed as a secondary objective. Results: A total of 479 studies were identified, of which 13 met the eligibility criteria. The results revealed improvements in functional performance, with increases in 6MWT in five studies, the TUG test in four trials, and better performance in the 5-STS and SC tests in five studies. Benefits in gait parameters were noted in four studies. Additionally, one of the articles reported improvements in static and dynamic balance, another showed enhanced proprioception, and a third described more efficient muscle activation during gait following hydrotherapy. Consistent benefits in pain reduction, joint stiffness, and activities of daily living, as reflected by VAS, WOMAC, and KOOS, were also noted immediately and maintained at follow-up. The variability in outcome measures and intervention characteristics limited the possibility of data integration and the calculation of effect sizes. Conclusions: Hydrotherapy as a rehabilitation intervention may be associated with improvements in functional capacity, mobility, and self-reported physical ability in patients with KOA, with some evidence supporting a beneficial effect on gait; however, the certainty of evidence remains low to moderate due to heterogeneity among studies and limited sample sizes. These findings should be interpreted in light of the methodological limitations identified across the included trials. Full article