Search Results (4,549)

To address the challenges of low accuracy and complex influencing factors in predicting horizontal well fracturing productivity during the development of unconventional oil and gas resources such as tight oil, this paper proposes a productivity prediction framework based on an improved feature selection method and an ensemble learning model. This study employs a fusion analysis using the entropy weight method to combine Pearson correlation analysis and improved gray relational analysis (IGRA) for feature selection. Thirteen machine learning models were tested with six distinct parameter combinations to construct a Stacking-based ensemble learning model, with base models including Random Forest (RF), Ridge Regression (RR), and Artificial Neural Network (ANN). Particle Swarm Optimization (PSO) was employed to optimize hyperparameters, followed by interpretability analysis using SHapley Additive exPlanations (SHAP). The results indicate that the model with fused weights demonstrated optimal performance. The Stacking model achieved significantly improved accuracy after PSO optimization, with the coefficient of determination increasing by 4.9%, outperforming all comparison models. Engineering guidance is provided: Under current geological conditions, sand ratio and displacement fluid volume require fine-tuning to prevent over-treatment. Fracturing design should implement differentiated strategies based on the target sand body thickness. This study not only delivers a high-precision production prediction tool but also offers decision support for efficient unconventional oil and gas field development through its exceptional interpretability. Full article

To address the limited in situ stress data and poor nonlinear fitting of existing methods, a Particle Swarm Optimization (PSO)–XGBoost inversion approach is proposed. XGBoost effectively models complex relationships between finite element results and measured stresses, leveraging its strong nonlinear mapping and suitability for small samples. PSO globally optimizes XGBoost hyperparameters, utilizing its fast convergence and global search capability. Combined with 5-fold cross-validation, this avoids empirical tuning errors and enhances generalization. The model uses finite-element-based stress-response values as inputs and calculates in situ stress data derived from hydraulic fracturing interpretations as targets. Engineering applications show that the PSO-XGBoost model outperforms common methods, achieving superior prediction accuracy and generalization with fast convergence. This offers a high-precision inversion approach for small-sample conditions, supporting engineering design and safety assessment. Full article

The large-scale accumulation of steel slag from steelmaking and the over-exploitation of natural aggregates pose significant environmental and resource challenges. Focusing on the arid-cold region of Xinjiang, China, this study proposes the use of steel slag as a substitute for natural aggregates in pavement engineering. Through experimental performance evaluation and regionalized life cycle assessment (LCA), the technical feasibility and carbon reduction potential of this application were comprehensively evaluated. Results indicate that steel slag asphalt mixtures meet or exceed specification requirements in terms of high-temperature stability, water stability, and low-temperature crack resistance. However, volume stability decreases slightly with higher steel slag content and finer particle size, necessitating pretreatment for long-term durability. A local life cycle assessment model considering regional transportation factors was applied to the G30 Luhuo Expressway project. During the materialization stage, steel slag was used to replace 30% of the natural aggregates, reducing approximately 6718 kg of carbon dioxide equivalent emissions (31.4%). This, to some extent, reduced the extraction of natural resources, saved land resources, and alleviated the problems of resource shortage and price fluctuations. Sensitivity analysis reveals a positive correlation between carbon reduction and steel slag content, while transport distance strongly influences overall benefits, with a critical threshold of about 78 km defining the effective utilization range. Furthermore, a multi-objective optimization model balancing service life, cost, and carbon reduction was developed to identify an optimal steel slag content scheme, maximizing comprehensive benefits under constrained conditions. This work confirms the technical viability of steel slag pavement in extreme climates and provides a systematic framework integrating environmental benefits and logistical constraints, supporting regional industrial synergy and promoting circular economy practices in low-carbon infrastructure. Full article

In order to guarantee sufficient growth, digestive stability, and long-term productivity in dairy heifers, proper nutritional management is crucial both before and after weaning. This case study assesses the impact of dietary modifications on growth performance and digestive parameters in commercial settings and details a field observation of concentrate overload in young Holstein heifers. From 77 to 165 days of age, the body weight (BW), average daily gain (ADG), body condition score (BCS), feed intake, and fecal characteristics of 15 calves were monitored. Infectious and parasitic causes of diarrhea were ruled out by fecal examinations. Ad libitum concentrate feeding resulted in low fecal scores with undigested grain particles and acidic smell, starch intake exceeding requirements, and concentrate intake reaching up to 6 kg as fed head×day. The BCS gradually rose, and ADG peaked at 1.64 kg/day. Forage intake increased, fecal consistency improved, and ADG stabilized after restricting concentrate allowance to 2.5% of BW. These results underline the significance of controlling starch intake and concentrate allowance to avoid excessive growth and digestive disorders in developing dairy heifers, and they support a nutritional basis for the observed digestive imbalance. Full article

A sustainable way to recycle used tires and improve the functionality of asphalt pavements is through the use of crumb rubber modified asphalt (CRMA). However, its application during high-temperature construction raises environmental and occupational health concerns due to the release of significant quantities of odorous and potentially harmful gases. Therefore, this study selected α-Amyl cinnamic aldehyde (ACA) as a deodorant and added it to CRMA at proportions of 0.5%, 1.0%, 1.5%, and 2.0% to prepare DCRMA. A number of common tests, such as softening point, ductility, penetration, Brookfield rotational viscosity, and segregation analysis, were used to evaluate the basic characteristics of the modified asphalt. A self-developed asphalt fume monitoring device was used to quantitatively analyze the changes in VOCs, H₂S gas concentration, and solid particle content in the asphalt fumes to assess the deodorization effect of ACA on CRMA. Furthermore, the deodorization mechanism of ACA on CRMA was explored in depth using microscopic methods, such as fluorescence microscopy (FM) and Fourier transform infrared spectroscopy (FTIR). The findings demonstrated that ACA can increase the softening point and viscosity of CRMA while decreasing its penetration and ductility. The storage stability was optimal at a 1.0% ACA addition. Additionally, as the ACA content increased, the concentrations of VOCs, H₂S gas, and solid particles in the asphalt fumes continued to decrease. FM results indicated that when the ACA content did not exceed 1.0%, it promoted the swelling degree of CR in the asphalt. FTIR results showed that ACA can reduce the characteristic peak intensity of CRMA. This study offers important technical references and practical support for the environmentally friendly use of CRMA. Full article

Chronic kidney disease (CKD) involves uremic toxin-driven tubular injury and systemic vascular dysfunction, in which mitochondrial impairment and apoptotic cell loss contribute to progressive tissue deterioration. Accordingly, a targeted EV platform is required to enable efficient miRNA delivery to the toxin-stressed tubular–endothelial compartment. Based on our previous study showing that melatonin restores miR-4516 levels under CKD-related stress, we directly loaded miR-4516 into engineered extracellular vesicles (EVs) to evaluate its effects on mitochondrial function and cell survival. Here, we engineered EVs with a G3-C12/RGD surface modification and established a miR-4516 loading strategy to enhance delivery to kidney proximal tubule cells and vascular endothelial cells. miR-4516 loading increased EV-associated miR-4516 levels without major changes in particle size distribution, and EV identity was supported by CD9 and CD81 expression. Confocal microscopy and flow cytometry demonstrated increased cellular uptake of miR-4516-loaded G3-C12/RGD-EVs compared with control EVs in TH1 proximal tubule cells and HUVECs. Under indoxyl sulfate stress, engineered EV treatment restored intracellular miR-4516 and improved mitochondrial function, as indicated by recovery of respiratory Complex I and Complex IV activities and improved Seahorse bioenergetic parameters (OCR/ECAR, basal and maximal respiration, ATP-linked respiration, and spare respiratory capacity). Annexin V staining further indicated reduced toxin-induced apoptosis. In an adenine diet-induced CKD mouse model, intravenous administration of miR-4516-loaded G3-C12/RGD-EVs improved urinary albumin-to-creatinine ratio (UACR), blood urea nitrogen (BUN), and serum creatinine. These findings indicate that miR-4516-loaded, targeting-engineered EVs may mitigate uremic toxin-associated mitochondrial dysfunction and renal impairment in CKD. Full article

Oil analysis is one of the main means to obtain the working status of important friction pairs in ship and Marine engineering equipment at present. Analyzing the wear mechanism by analyzing the particle size, morphology, properties and other characteristics of metal abrasive particles in the oil is an important basis for achieving health monitoring and scientific maintenance of ship and Marine engineering equipment. Classifying the abrasive particles in the oil according to their particle size is an important step in sample pretreatment. This paper proposes a two-stage sorting microfluidic chip for wear debris based on magnetophoresis. By setting up external permanent magnets in a stepwise manner in the primary and secondary sorting areas, gradient magnetic fields of different magnitudes were formed. The effects of different sample flow rates, sheath fluid flow rates and sheath flow ratios on the pre-focusing before sorting and the sorting effect were studied. The primary sorting of ferromagnetic metal wear particles larger than 50 µm and the secondary sorting of those smaller than 50 µm have been achieved. The primary sorting can serve as an early warning for abnormal equipment wear, while the secondary sorting can provide data support for the scientific formulation of maintenance plans based on equipment requirements. This work provides a new idea and method for the rapid determination of lubricating oil contamination in engineering equipment. Full article

This study presents an analytical investigation of the dynamic behavior of concrete beams reinforced with different types of nano-clay (NC) particles and resting on a Winkler–Pasternak elastic foundation. The equivalent elastic properties of the nanocomposite were determined using an Eshelby-based homogenization model. An improved quasi-three-dimensional beam theory was applied to formulate the governing equations of motion, which were subsequently then analytically solved using Navier’s method. The analysis shows that NC reinforcement systematically elevates the natural frequencies of the beam, with the magnitude of improvement varying by particle type and concentration. Increasing the NC volume fraction to 30% leads to a significant rise in the fundamental frequency, reaching about 30% for hectorite (SHca-1) compared with the unreinforced beam, whereas montmorillonite (SWy-1) produces a more moderate increase of approximately 13%. This reinforcing effect remains consistent across different span-to-depth ratios, indicating that the influence of nano-clay content on the dynamic response is largely independent of beam slenderness. Furthermore, increasing the Winkler foundation stiffness results in an almost linear rise in frequency of approximately 18–22%, whereas the Pasternak shear parameter produces a stronger effect, reaching around 25% enhancement depending on the reinforcement type. These results indicate that incorporating nano-clay platelets can be an effective strategy for enhancing the vibrational stiffness of concrete beams and improving their dynamic performance when interacting with supporting soil media. Full article

With the rapid development of smart cities, coordinating diverse distributed energy resources through storage-centric shared management has become a critical challenge. This paper proposes a bi-level energy management framework to support peer-to-peer energy trading among multiple virtual power plants (VPPs) under multidimensional uncertainties. The interaction is modeled as a Stackelberg–Nash equilibrium framework, in which OK, we will make the necessary revisions as per the requirements.a public energy storage operator and a natural gas company act as leaders to maximize social welfare and design differentiated trading strategies for VPPs. The VPPs act as followers and participate in cooperative energy trading based on a generalized Nash equilibrium scheme, sharing surplus energy and allocating cooperative benefits according to their contributions. To address uncertainty, Conditional Value at Risk (CVaR) is adopted to quantify the expected loss of the upper-level decision makers. The lower-level VPP problem is formulated as a three-stage stochastic robust optimization model considering renewable generation uncertainty. To solve the resulting nonlinear bi-level problem, a two-stage solution approach combining particle swarm optimization and KKT-based reformulation is developed to transform it into a tractable mixed-integer linear programming model. Numerical case studies verify the effectiveness of the proposed framework. Full article

Long-term operation of drip emitters under sediment-laden water conditions readily induces particle deposition and clogging, leading to discharge reduction and deterioration of irrigation uniformity. To clarify the temporal evolution and spatial distribution of clogging and to support structure-oriented anti-clogging improvement, three integrated drip tape emitters with different labyrinth-channel geometries were tested at sediment concentrations of 1, 2, and 3 g·L⁻¹ under a constant pressure of 100 kPa. The average relative discharge ratio (Dra) and Christiansen’s uniformity coefficient (CU) were continuously monitored, and cross-sectional observation and numerical simulation were combined to identify dominant deposition hotspot regions within the labyrinth channel. The results showed that increasing sediment concentration significantly accelerated clogging development and shortened operating lifetime. At 1 g·L⁻¹, the times required for the three emitter types to reach the clogging criterion of Dra < 75% were 120, 81, and 107 h, respectively, whereas at 3 g·L⁻¹ these values decreased to 39, 42, and 39 h. CU continuously declined with operating time and, in some treatments, responded earlier than Dra to system deterioration. Sediment deposition was mainly concentrated in the inlet section and bend regions, indicating that these locations were the dominant hotspots for clogging initiation and propagation. These findings demonstrate that clogging in drip emitters is jointly regulated by sediment load and labyrinth-channel geometry, and that hotspot-based structural optimization provides an effective basis for improving anti-clogging performance under sediment-laden water conditions. Full article

The pods of pea (Pisum sativum L.), an abundant agroindustry by-product, represents a sustainable source of bioactive compounds. To harness these compounds effectively, this study aimed to optimize the ultrasound-assisted extraction (UAE) of polyphenols and plant pigments (chlorophylls and carotenoids) from pea pod waste using response surface methodology, and to evaluate the encapsulation of the resulting extract with a novel pea-based carrier derived from whole pea grain powder. The optimal conditions for the extraction were a time of 45 min, a solid-to-solvent ratio of 1:48 (w/v), and an ethanol concentration of 58.51% (v/v). The extract obtained under these conditions was encapsulated using pea grain powder and compared with a conventional whey protein carrier. The resulting microencapsulates were characterized in terms of process yield, moisture content, particle size distribution, thermal properties, and phenolic composition. Pea grain powder as a carrier provided higher powder yield, lower moisture content, and improved thermal stability, whereas whey protein allowed slightly higher retention of most bioactive compounds, except for coumaric acid and kaempferol. Overall, these findings highlight pea grain powder as a promising plant-based carrier that supports the valorization of pea pod waste, contributing to the development of sustainable ingredients and a circular economy for legume processing by-products. Full article

Tailings backfilling (TB) is widely recognized as an environmentally friendly and engineering safe technique to enhance mining efficiency. However, the heterogeneous particle distribution in TB slurry, also-named the segregation phenomenon, can significantly affect the mechanical strength of the backfill, especially under high goaf conditions. Therefore, elucidating the spatial distribution characteristics of particles during high-goaf filling has become a crucial research focus for improving the mechanical behavior of tailings backfill. A systematic experimental investigation was conducted in this study, incorporating the similarity principle, to analyze the migration behavior of backfill slurry particles and to clarify how the different backfill heights influence the spatial distribution of fine, medium, and coarse particles. The results indicate a clear vertical variation in PSD. Based on statistical analysis of samples collected from different backfill height experiments, coarse particle content increased progressively from the upper to lower layers (median: 16.2%, 23.6%, and 25.0%), while medium-sized particles remained relatively stable (37.0%, 37.3%, 37.0%). Fine particles dominated overall but decreased with layers (45.6%, 38.8%, 38.3%). Coarse particles tended to settle downward due to gravitational forces, whereas fine particles migrated upward. The distribution of medium-sized particles remained largely homogeneous. Fine and coarse particles were subjected to opposing driving forces. Meanwhile, particles maintained an approximately symmetrical distribution in the horizontal direction. Moreover, when the backfill height exceeded 800 mm, a notable intensification of stratification occurred, indicating a strong height-dependent transition in segregation behavior. In contrast, in the horizontal direction, the PSD showed no clear dependence on backfill height. These findings provide new insights into the mechanisms of particle segregation within backfill materials, offering a theoretical foundation and experimental support for optimizing PSD within the backfill body and elucidating the collapse mechanisms of high goafs. Full article

The stability of subsea tunnels is governed by the strong coupling among stress redistribution, damage evolution, and seepage flow (Stress–Damage–Seepage, SDS). The dynamic interplay, especially under high water pressure, often leads to catastrophic failures, yet its mechanisms, particularly the role of support timing, remain insufficiently understood due to limitations in conventional numerical methods. This study aims to unravel the SDS coupling mechanisms during tunnel excavation under high hydraulic head, and to quantitatively investigate how support timing influences the stability of the surrounding rock within this coupled system. A coupled Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) framework was employed. In this approach, excavation-induced damage, crack propagation, and fluid–particle interactions are explicitly resolved at the particle scale, whereas the macroscopic permeability evolution is captured through an imposed empirical exponential relationship. Simulations were conducted under both steady-state and transient seepage conditions with varying stress ratios and water heads. High-head transient seepage intensifies SDS coupling, dynamically redistributing seepage forces to damage zone edges and amplifying damage. Support timing critically mediates this interaction: premature support risks tensile failure at the tunnel periphery, while delayed support allows a vicious cycle of shear failure and increased inflow. Optimal “timely” support, applied after initial deformation, diverts high seepage forces inward, minimizing final damage. The spatiotemporal synchronization of transient seepage forces with damage evolution is pivotal for stability. Support timing acts as a key control variable. The CFD-DEM framework effectively elucidates these micro-mechanisms, providing a scientific basis for the dynamic design of support in high-pressure subsea tunnels. Full article

Cartilage regeneration remains an unmet clinical challenge. Despite the great advances in the production of hydrogels as support matrices for cartilage regeneration, the resulting mechanical properties remain low. Granular composite hydrogels appear as ideal candidates due to their injectability and modularity in design. Here, we report on the fabrication and characterization of heterogeneous composite granular hydrogels based on methacrylated chitosan (CHIMA) and gelatin (GelMA) microparticles supported by an interstitial methacrylated alginate (ALMA) matrix. Microparticles were prepared by an oil-emulsion method and their size and morphology optimized, resulting in CHIMA and GelMA microparticles of 10.8 µm (95% CI 9.2, 13.1) and 115.8 µm (95% CI 107.5, 137.6) in diameter, respectively. The microparticles were mixed with ALMA and crosslinked to form granular hydrogels that demonstrated reduced swelling and weight loss. The storage modulus increased from 33 to 66.4 kPa for CHIMA/ALMA hydrogels and from 11.5 to 19.5 kPa for GelMA/ALMA hydrogels when the particle concentration increased from 10 to 50%, and was higher than traditional ALMA hydrogels. Hydrogels of 50:50 CHIMA:GelMA permitted a 6.6-fold increase in cell number after 28 days of culture, and promoted the chondrogenic differentiation of embedded mouse mesenchymal stem cells with a glycosaminoglycan deposition of over 15 µg and the expression of chondrogenic markers. Full article

The advancement of sustainable construction requires the development of earthen materials compatible with 3D printing (additive manufacturing), along with specified engineering standards. Many existing studies improve workability and early strength using chemical stabilizers such as cement; however, these additives increase embodied carbon and undermine sustainability objectives. Challenges remain in the formulation of an earthen mixture that satisfies both printability and structural requirements for large-scale construction. Previous earth-based mixes have reported excessive shrinkage and inadequate compressive strength. This study presents the systematic optimization of a low-carbon, 3D-printable earthen mixture using locally sourced clay-loam soil from Belén, New Mexico (NM). The soil was modified with graded concrete sand and rice hull fiber to improve printing parameters such as buildability, extrudability, and printability while meeting the NM Earthen Building Code requirements for compressive and flexural strength. Soil characterization tests (particle size distribution, consistency, optimal water content) guided iterative refinement to enhance dimensional stability and mechanical performance. A baseline 2:1 soil-to-sand ratio (max aggregate size No. 4) was established. Incorporating $2\%$ rice hull fiber and reducing max aggregate size to No. 16 (S67F2) early-age shrinkage was reduced from $12.33\%$ to $3.48\%$ ($72\%$ reduction) while maintaining a 28-day compressive strength exceeding 660 psi, more than twice the code minimum. The optimized mixture supported 24 printed layers without deformation, achieved 189 psi flexural strength (three times the code minimum), and produced a stable 2-ft-diameter dome with minimal cracking. Full article