Search Results (5,005)

Bubble curtains are non-physical fish-guidance devices that modify the hydrodynamic and acoustic environment near water intakes. This study quantified the liquid-phase velocity field generated by a bubble curtain placed in the vicinity of a water intake in a laboratory open-channel testing rig using planar Particle Image Velocimetry (PIV). Measurements were carried out at a background water velocity of 0.33 m/s for air-injection rates of 0, 5, 8, 10.5, and 15 L/min. Velocity fields were obtained at distances of 0, 20, 30, and 50 mm from the porous hose, with detailed analysis performed at 20 mm. Bubble regions were identified and masked before liquid-phase image correlation. Air injection modified the local velocity direction and produced localized velocity increases, with a maximum local liquid-phase velocity magnitude of approximately 0.42 m/s. Relative to the no-airflow reference velocity of 0.33 m/s, the spatially averaged velocity magnitude increased by approximately 6.7%, 11.8%, 15.2% and 16.7% at airflow rates of 5, 8, 10.5 and 15 L/min, respectively; however, the incremental increase between consecutive airflow conditions decreased from approximately 4.7% between 5 and 8 L/min to 3.1% between 8 and 10.5 L/min and 1.3% between 10.5 and 15 L/min. The spatially averaged velocity magnitude increased with airflow rate, while the incremental response decreased progressively at higher air-injection rates. Thus, 8 L/min represents a candidate energy-efficient operating condition under the tested laboratory conditions. The results provide hydraulic information relevant to subsequent fish-behavior experiments; however, fish-guidance performance cannot be inferred from the present hydrodynamic measurements alone. The results provide a hydraulic basis for designing subsequent fish-behavior experiments. Because no fish were present during the measurements, the study does not assess fish attraction, avoidance, movement restriction, passage, entrainment, or guidance efficiency. Fish-guidance performance cannot be inferred from the present hydrodynamic measurements alone. Full article

Background: Biodegradable microspheres (MSs) are good candidates for intravitreal administration in the posterior segment of the eye. MSs can be formulated as injectable preparations and administered using syringes with small-gauge needles. To allow proper injectability and avoid patients’ discomfort, the MS size should be as small as possible. However, the relationships between size, encapsulation efficiency, and drug-release behavior in these systems are widely recognized. Methods: In an attempt to optimize this requirement, we present here interesting dexamethasone (Dxm), vitamin E and human serum albumin (HSA) biodegradable MSs in the 2–20 µm range, elaborated by employing a version of the single-emulsion extraction–evaporation method. The method employed here renders MSs in the 2–40 µm range. The present work focuses on evaluating the smaller fraction, the 2–20 µm range, including physicochemical characterization, image analysis, dexamethasone release assays, cytotoxicity, and injectability evaluations. Results: The 2–20 µm fraction represents 25–30% of the entire population, has an average particle size of 18 µm, is spherical in shape, and has a Dxm loading between 38 and 50 µm per mg of MSs. In addition, a comparative evaluation between both fractions was carried out to assess whether relevant therapeutic differences can be expected. The in vitro release studies showed that MSs sized 2–20 µm, when vitamin E and HSA were included, have a low burst effect and, after that, a biphasic release profile during the first 4 weeks, with a long sustained Dxm release phase. This suggests that they might be better suited to maintain therapeutically anti-inflammatory concentrations of Dxm in the vitreous than the 20–40 µm MSs fraction, which also had a controlled Dxm release but in very reduced amounts after the first week. Conclusions: This 2–20 µm MS system might represent a success for its advantages over the existing alternatives in the marketplace, such as dexamethasone implants. Among others, due to the minimized risk associated with their administration that does not need ocular surgery, and consequently, the better the patient’s adherence is expected, there can be a medical preference for this system for its ease of use and possibility of personalizing the dose. Full article

Extending the lean operating limit of small-bore gasoline direct-injection (GDI) engines offers a practical pathway to improve fuel conversion efficiency in the light-duty transportation segment; however, deteriorated flame propagation in lean gasoline limits stable operation. The present investigation experimentally examines green hydrogen enrichment as an enabler of extended lean operation in a 390 cm³ single-cylinder air-cooled GDI engine at excess-air ratios (λ) of 1.15 and 1.22, with hydrogen energy fractions of 0–5.8% inducted through the intake manifold, at 3000 rpm, wide-open throttle, and maximum-brake-torque spark timing. Under pure-gasoline operation at λ = 1.22, the coefficient of variation of indicated mean effective pressure reached 5.23%, surpassing the 5% limit for stable combustion, while adding just 1.5% hydrogen was sufficient to bring the engine back to stable operating conditions. When hydrogen enrichment was raised to its upper limit of 5.8% at the same lean condition, peak in-cylinder pressure rose by 15%, the flame-development duration shortened by 20%, and combustion phasing returned to the target window of 8–12 °CA aTDC. In addition, brake thermal efficiency climbed from 26.55% to 29.25%. In terms of emissions, CO and HC decreased by 53.6% and 21.4%, respectively, while NOx increased moderately by 8.3%. However, the brake-specific CO, HC, and NOx decreased by 65.4%, 41.4%, and 19.3%, respectively; the NOx reduction arose despite a modest rise in the measured concentration. Therefore, the 5.8% hydrogen addition at λ = 1.22 is the best-performing operating condition, demonstrating the balanced nature of hydrogen-assisted lean-burn combustion, where hydrogen restores combustion quality while extended leaning controls the thermal and emission penalties. Full article

Background: The continuous emergence of antigenically distinct SARS-CoV-2 variants of concern (VOCs) necessitates the development of versatile and effective vaccine platforms capable of inducing broad and sustained immunity. Methods: We designed a chimeric trivalent recombinant protein, TriRBD, incorporating the receptor-binding domains (RBDs) of the Delta, Omicron BA.1, and XBB.1 subvariants. To enhance delivery efficiency and immunogenicity, TriRBD was formulated into a dissolving hyaluronic-acid-based microneedle array patch (MAP) using the droplet extension (DEN) technique. We investigated the synergistic effects of two squalene-based oil-in-water (O/W) emulsions, SqTS (Squalene/Tween-80/Span-85) and SqT (Squalene/Tween-80), as adjuvants within the MAP after gamma-irradiation sterilization, alongside safety evaluations via rabbit skin tests. Results: The SqTS-adjuvanted MAP formulation was found to be non-irritating. Immunogenicity studies in BALB/c mice revealed that MAP-delivered TriRBD elicited significantly higher and more durable IgG endpoint titers (EPT) compared to intramuscular injection, with robust antibody levels sustained for up to 52 weeks. Notably, the irradiated SqT-adjuvanted MAP group exhibited a highly balanced Th2/Th1 immune response (IgG1/IgG2a ratio), while the irradiated SqTS-adjuvanted MAP group shifted toward a Th2-preferred against TriRBD. Although the EPT against the Omicron BA.1 variant was relatively lower, the irradiated MAP-SqT-TriRBD group elicited significantly both of IgG1 and IgG2a, resulting in a balanced and broadened antibody repertoire. Conclusions: These findings demonstrate that combining a trivalent RBD antigen with a SqT-adjuvanted MAP platform provides a potent, safe, and thermostable strategy for broad-spectrum protection against evolving SARS-CoV-2 variants and future pandemic threats. Full article

Physiological-signal-based emotion recognition has received attention in human–computer interaction. Electrocardiograms (ECGs) are readily acquired, and short windows contain repeated beat morphology and beat-wise variations that single-window encoding struggles to separate. Multiscale morphology modeling and training-sample diversity remain limited. We therefore propose Complementary Feature Fusion Dual-Path (CFF-DP), an ECG emotion recognition framework using beat-level complementary feature fusion, with three components: (1) a dual-path framework, where the morphology-stable path constructs representative beats with window-adaptive Gaussian weights, while the morphology-difference path combines beat-wise encoding, positional encoding, and additive attention; gated fusion integrates representations; (2) adaptive dilated convolution (ADConv), which extracts multiscale beat-morphology features using shared kernels and input-dependent scale weights; and (3) deviation-based beat-oriented augmentation (DBOA), which adjusts real-noise injection probability and target signal-to-noise ratio according to morphological deviation. CFF-DP achieved 43.39% mean Macro-F1, close to the best comparator, with the fewest multiply–accumulate operations in five-seed WESAD three-class leave-one-subject-out (LOSO) evaluation, although recognition mainly distinguishes stress, with limited amusement discrimination. With short-gap calibration and testing within the same recording, fine-tuning using 40 s per class achieved 76.72% Macro-F1, exceeding six comparators. Binary DREAMER LOSO retained WESAD hyperparameters: valence Macro-F1 exceeded six comparators, whereas arousal fell below four; both remained below uniform random baselines, indicating limited recognition under current experimental conditions. The framework combines computational efficiency with within-record personalization advantages, although cross-subject recognition remains limited. Full article

Depleting fossil reserves and tightening emission limits have driven interest in plant-derived diesel blend fuels. This work evaluates tea tree oil (Melaleuca alternifolia) at 5, 10, 15 and 20 vol% in diesel through GC–MS characterisation, suspended-droplet combustion and single-cylinder engine testing. GC–MS resolved between 182 and 204 peaks per sample; eight monoterpene constituents were tracked, of which terpinen-4-ol was the largest peak in the neat oil at 21.81 area %. The oxygenated fraction rose from 19.07 to 20.85 area % between TTD5 and TTD20, raising fuel-bound oxygen from approximately 0.28 to 1.13% by weight, while the derived cetane number of the blends fell from 43.2 to 36.6. Droplet tests produced stable cone-shaped flames with ignition delays of 2–3 s and burn durations of 4–6 s, with micro-explosive burning from TTD10 onwards attributed to the volatility differential between the terpene and diesel fractions. In the engine, the longer ignition delay displaced combustion later in the cycle: CA10 referenced to injection rose from 8.7° for neat diesel to 18.4–20.5° for the blends, peak net heat release from 59.9 to 94.7 J/°CA and peak cylinder pressure from 72 to 88.7 bar, while the CA10–CA90 duration remained constant at 27–30 °CA. Brake thermal efficiency rose from 28.9 to 30.1% at full load and by 2.6 percentage points at part load. Brake-specific CO and hydrocarbons fell by 30.5 and 27.8%, and smoke by 24%, while NOx rose by 17.4%. A normalised multi-criteria assessment identified TTD15 as the preferred blend. Full article

The shale oil reservoirs in the Sichuan Basin are distinguished by pronounced heterogeneity, with natural fractures locally developed within specific horizontal well intervals. These fractures serve as pivotal conduits for crude oil migration; consequently, maximizing connectivity with these pre-existing discontinuities to enlarge the Stimulated Reservoir Volume (SRV) remains a paramount objective in hydraulic fracturing design. In early-stage field operations, temporary plugging fracturing was routinely implemented in horizontal wells to establish effective linkage with natural fractures. However, critical treatment parameters—including the type of Temporary Plugging Agent (TPA), plugging location, and pumping rate—were predominantly determined via empirical approaches. This heavy reliance on field heuristics often led to suboptimal diversion performance and substantially undermined overall stimulation efficiency. To address these limitations, we employed a three-dimensional dynamic temporary plugging evaluation system equipped with wedge-shaped fracture models of varying apertures (specifically 6 mm, 4 mm, and 2 mm) to systematically screen high-strength TPA combinations. This experimental setup enabled the simulation of realistic fracture geometries under dynamic flow conditions. The screening results revealed a clear inverse correlation between fracture width and plugging efficacy: for any given TPA formulation, the achieved plugging pressure differential decreased progressively as the fracture aperture expanded from 2 mm to 6 mm. Furthermore, under a constant fracture width, the incorporation of smaller-sized TPA particulates into the formulation proved critically effective in substantially elevating the plugging pressure, attributable to the enhanced bridging and packing efficiency within the narrower constrictions. Through this rigorous, width-dependent optimization protocol, the final optimized TPA blend consistently generated a plugging pressure differential exceeding 24 MPa, thereby robustly validating its capacity to induce effective fracture diversion. In parallel with the experimental efforts, a numerical simulation model was developed to systematically optimize the plugging position, injection rate, and target plugging pressure. The proposed workflow was subsequently applied to Well XN1. Post-treatment diagnostic analysis indicated that the temporary plugging operation markedly enhanced the extent of fracture propagation, thus validating the effectiveness of the optimized strategy. Full article

High-speed autonomous navigation of micro aerial vehicles (MAVs) is essential for inspection tasks in restricted spaces (e.g., dense industrial facilities or narrow corridors), where reliable spatial perception and stable flight control are required. However, existing deep reinforcement learning-based navigation methods often suffer from delayed obstacle avoidance responses due to the low fitting efficiency of raw geometric distance representations for dynamic threats, trigger control oscillations that disrupt flight stability due to an over-reliance on external hard-clipping mechanisms, and frequently fall into local optima such as obstacle-edge hovering driven by heuristic penalties, thereby reducing overall navigation success rates and training efficiency. We propose PR-Nav, an agile navigation framework combining potential-field-augmented perceptual representation with a physics-modulated probabilistic action manifold. PR-Nav comprises three components: (1) a potential-field-augmented ray tensor representation that nonlinearly maps raw distance information into physical repulsive gradients to improve the policy network’s fitting efficiency for dynamic threat boundaries; (2) a physics-prior-modulated Beta action manifold that injects local potential-field gradients as residual biases into the probability density generation process, replacing external hard clipping with internal network constraints to reduce the action smoothness index (ASI); and (3) a potential-based reward shaping (PBRS) mechanism that replaces traditional heuristic penalties with global physical potential energy differences to improve the navigation success rate in complex environments and accelerate policy convergence. Experiments on the high-fidelity Isaac Sim simulator and a real-world physical flight platform show that PR-Nav achieves an overall navigation success rate of 96.5%, outperforming the strongest competing method by 10.8 percentage points. In quantitative evaluations of flight smoothness and training efficiency, its action smoothness index (ASI) is reduced to 4.25 ${\mathrm{m/s}}^3$ and it achieves an approximate 54% reduction in convergence steps compared to the baseline, the best results among the compared methods. Ablation studies verify the contribution of each component to its corresponding metrics. These results demonstrate that combining physical potential field modeling with underlying probability distribution reconstruction is an effective route to robust and agile navigation in dynamic restricted spaces. Full article

This paper proposes a control strategy for a modular multilevel converter (MMC)-based photovoltaic (PV) system operating under non-homogeneous irradiance and unbalanced grid voltage conditions. The considered topology integrates PV units directly into the MMC submodules, enabling distributed maximum power point tracking (DMPPT). The proposed control framework combines a generalized grid controller with dedicated AC and DC circulating current controllers to manage for vertical and horizontal power imbalances, respectively. The grid controller accommodates different operating objectives, namely balanced grid current injection, constant instantaneous real power operation, and constant instantaneous imaginary power operation, while regulating the injected total three-phase active and reactive powers to their prescribed references. The AC circulating current controller is formulated by extending a single-phase approach independently to each converter leg, thereby achieving complete decoupling among the legs in the management of vertical power mismatch under general grid unbalance conditions. Furthermore, the proposed DC circulating current controller simultaneously handles for power imbalances originating from both partial shading among the converter legs and grid voltage unbalance. The effectiveness of the proposed approach is assessed through detailed simulations under both homogeneous and non-homogeneous irradiance conditions and for different grid control objectives. The results demonstrate effective maximum power extraction, proper regulation of the internal power flows, and stable converter operation under unbalanced grid conditions, yielding an overall system efficiency greater than 97% while fulfilling the desired grid power control objectives. Full article

Produced water (PW) from oil and gas extraction represents a critical sustainability challenge: billions of barrels annually generate high-salinity waste streams with hydrocarbon contaminants, creating severe environmental and economic burdens through disposal costs, ecosystem contamination, and water scarcity exacerbation. Conventional treatment options deep well injection, evaporation ponds, and reverse osmosis (RO) demand substantial energy inputs and capital investment, limiting circular-economy adoption in resource-constrained regions. Forward osmosis (FO) emerges as a more sustainable alternative, leveraging osmotic gradients to reduce energy consumption and fouling compared to pressure-driven RO, yet selecting environmentally and economically viable draw solutions remains critical. This work advances a circular economy approach by evaluating PW itself as a low-cost, on-site draw solution for FO, thereby transforming waste into a resource. Performance was compared against six synthetic salts (NaCl, KCl, MgCl₂, CaCl₂, NaNO₃, (NH₄)₂SO₄) using ultrapure water and microalgal suspensions as feeds. Results demonstrated that PW performed osmotically equivalent to NaCl despite multicomponent composition, validating its reusability. With microalgal feed, membrane-interface osmotic pressure reached 51.2 bar versus 8.43 bar in bulk solution, attributed to concentration polarization from biomass accumulation and extracellular polymeric substances. Importantly, effective osmotic driving force reached 7.80 bar with 48.3% flux efficiency, surpassing MgCl₂, CaCl₂, NaNO₃, and (NH₄)₂SO₄. This study demonstrates that PW-driven FO coupled with microalgal cultivation provides a genuinely sustainable pathway for simultaneous produced-water recovery, biomass concentration, nutrient recovery, and wastewater valorization, supporting circular economy principles and reducing both environmental impact and operational costs in oil and gas operations. Full article

In high water-cut reservoirs, water flooding efficiency declines due to high-permeability channels that aggravate heterogeneity and cause water channeling. Gas flooding technology can improve recovery but is limited by operating conditions and costs. Water-alternating-gas (WAG) injection combines the advantages of both methods, but the complex reservoir connectivity and the strong inter-well interference hinder accurate displacement path control, which will reduce the oil production efficiency and increase costs. In this paper, a reinforcement learning-based dynamic optimization strategy is proposed to solve the injection optimization problem for WAG injection with inter-well connectivity. Specifically, a net present value (NPV) model is built for a single time slot based on the oil production, the injection cost of water or gas, the conversion cost between water flooding and gas flooding, and the inter-well connectivity. Furthermore, an NPV optimization problem is formulated for multi-injection wells and multi-production wells to enhance oil recovery. Then, a Q-learning algorithm is adopted for solving the proposed optimization problem to achieve the optimal WAG injection strategy, in which the state space comprises pressure and three-phase saturation, the action space includes injection type and rate, and the reward function is the total recovery benefit. Finally, extensive numerical simulations are conducted. Quantitative results demonstrate that the proposed algorithm achieves a converged NPV of approximately $8.3 million, outperforming the fixed-rate WAG strategy by 3.75%, the water flooding strategy by 9.21%, and the gas flooding strategy by 12.16%. Moreover, the proposed method increases cumulative oil production by 4.6% over fixed-rate WAG, 12.8% over water flooding, and 18.7% over gas flooding, while maintaining a competitive water cut of 0.734. The experimental results imply that the proposed WAG strategy can obtain higher NPVs than that of the benchmark algorithms. Full article

The precessing vortex core (PVC) in the draft tube of a Francis turbine at part load produces severe pressure pulsations that threaten structural integrity. Efficient active control of PVC demands an understanding of how momentum injection alters the spatial topology and coherent energy of this global instability. This experimental study, conducted on a canonical expanding swirling flow with ten actuators delivering axial, radial, and combined jets, employs synchronized planar PIV and wall-pressure measurements to capture the velocity and pressure fields. Robust correlations are obtained: on-axis and vortex core tangential velocity fluctuations are linearly coupled, circulation scales linearly with precession radius, and helical pitch increases as the precession orbit contracts. Notably, the wall-pressure amplitude depends quadratically on the PVC’s turbulent kinetic energy contribution, showing that spatial contraction enhances the attenuation. These interlinked scaling laws provide a physics-based framework connecting control input to vortex reconfiguration and dynamic load, guiding low-energy control design for hydraulic turbines and other swirling flow devices. Full article

To obtain a better insight into the displacement efficiency in heterogeneous reservoirs, a cross-sectional study for a pair of vertical injection and producing wells is considered. Geostatistical modeling is employed to simulate various cases of realistic reservoir heterogeneity between the wells. This is coupled with reservoir simulations of immiscible displacement to evaluate the sweep efficiency. Two groups of similarity criteria characterizing the heterogeneous lithology distribution and the fluid flow are proposed. One group is used to distinguish and delineate the limiting cases of homogeneous and layered reservoirs. The other group is used to distinguish and constrain the limiting cases of gravity-driven flow and displacement in anisotropic reservoirs. The main conclusions of this study are obtained using a parametric investigation into the displacement efficiency in various reservoirs. Furthermore, the uncertainty propagating from reservoir heterogeneity to the efficiency is addressed. It is shown that the displacement is generally more efficient in the reservoirs built of thin and extended interlayers. It is also more efficient at larger net-to-gross ratios; however, in a specific limiting case of a large buoyancy force, an optimal net-to-gross ratio exists. The physical mechanisms resulting in such optimal values and their potential applications in well placement are discussed. Full article

Trifluoroacetic acid (TFA), the shortest perfluoroalkyl carboxylic acid, is the most prevalent ultra-short-chain PFAS in the environment. Its high polarity, strong acidity, water solubility, persistence, and mobility promote widespread occurrence across aquatic, terrestrial, agricultural, food, plant, and biological matrices. These same properties make reliable determination challenging because TFA shows poor reversed-phase retention, limited enrichment potential, few confirmatory ions, and frequent laboratory/background contamination. This review critically evaluates extraction and analytical strategies for TFA determination, including direct injection, dilute-and-shoot, SPE, solvent-based extraction, LC-MS/MS, IC-MS/MS, HILIC and mixed-mode LC-MS/MS, CE-MS/MS, HRMS, and fluorine-balance approaches. No single method is universally optimal: background contamination is often limited in low-concentration water samples, extraction efficiency dominates uncertainty in soils, plants, and foods, and ion suppression is critical in biological fluids. Direct injection is generally preferable for clean water and supports interlaboratory-validated methods, whereas complex matrices require matrix-specific extraction, with acetonitrile/water and isotope dilution among the most reliable options. Acidified methanol may cause esterification artifacts, and SPE methods adapted from long-chain PFAS are often unsuitable. The review proposes a matrix-specific extraction hierarchy and a minimum reporting checklist to improve harmonization and data comparability. Full article

Low-temperature CO₂ fracturing generates obvious thermal tensile disturbance via reservoir–fluid temperature difference, which is an efficient stimulation technology for hot dry rock (HDR). In this work, a two-dimensional plane-strain thermo-hydro-mechanical-damage (THMD) coupling numerical model considering granite mechanical heterogeneity is established, and seven single-variable simulation cases are designed to quantitatively analyze the joint effects of fluid type, reservoir temperature, injection parameters, and in situ stress on HDR damage, temperature-pore pressure field, and system energy evolution. The results show that the damaged area induced by CO₂ injection is five times larger than that of water under identical baseline conditions. Raising reservoir temperature or injection pressure significantly strengthens thermo-seepage coupling effects, with the maximum damaged area ratio increased by over 220%. Higher CO₂ injection pressure and lower injection temperature weaken thermal stress and restrain fracture propagation; an anisotropic stress field only produces a single main fracture without complex branch networks. Energy analysis indicates injection pressure dominates the accumulation of HDR strain potential energy, and the potential energy under high injection pressure can reach more than 11 times the baseline value. This study quantitatively analyzes the individual influences of fluid type, reservoir temperature, injection temperature, injection pressure, and in situ stress anisotropy on HDR damage evolution, and discusses their combined effects. Full article